[{"data":1,"prerenderedAt":376},["ShallowReactive",2],{"$fgukOamtKU1RtUiMFsqdObttmqPPQz0uc7bl_gj_LyX0":3,"$fbaXVfDVkdv-y_0biJ_jChAx8E3jcWulZW5AkWe6jREw":245,"article-68":375},{"code":4,"msg":5,"data":6},0,"",{"category":7,"tag":11,"popular":19,"latest":86,"banner":126,"list":151,"cache":244},[8,9,10],"Agent","OpenAI","LLM",[8,12,13,14,9,10,15,16,17,18],"Google","Nvidia","Claude","DeepSeek","OCR","Chat","Generator",[20,29,37,45,54,62,70,79],{"id":21,"publish_date":22,"is_original":23,"collection":5,"cover_url":24,"cover_url_1_1":25,"title":26,"summary":27,"author":28},411,"2023-09-10",1,"article_res/cover/451ef50c225a8dc61c4336506794d13b.jpeg","article_res/cover/3ba9dc7a72f87d40b20fc2d225289ee3.jpeg","Idealism","Reality is created by the mind, we can change our reality by changing our mind. - Plato","Renee's Entrepreneurial Journey",{"id":30,"publish_date":31,"is_original":23,"collection":32,"cover_url":33,"cover_url_1_1":34,"title":35,"summary":36,"author":28},108,"2024-12-07","#LLM #AGI #AI Agent","article_res/cover/0039044422e4ec9f61c18e8ee1693bb0.jpeg","article_res/cover/4220971b108a91d21407d87bb02fbaa6.jpeg","Freysa.ai: The World's First Adversarial AI Agent Game","说服 Freysa 把钱包里的钱都拿出来",{"id":38,"publish_date":39,"is_original":23,"collection":40,"cover_url":41,"cover_url_1_1":42,"title":43,"summary":44,"author":28},12,"2025-03-09","#Oxford #Reasoning #LLM #Tool Use","article_res/cover/d448e9b3617a0b5302e1bd10c438bca9.jpeg","article_res/cover/864a468f9cc4c9317efadb3811909888.jpeg","Agentic Reasoning Framework - Significantly enhance the reasoning ability of LLMs through the integration of external tools using agents","Agentic Reasoning: Reasoning LLMs with Tools for Deep Research",{"id":46,"publish_date":47,"is_original":4,"collection":48,"cover_url":49,"cover_url_1_1":50,"title":51,"summary":52,"author":53},480,"2023-04-14","#Stable Diffusion","article_res/cover/0bdbe7cb1de4a78e54536e5d9afa7ec9.jpeg","article_res/cover/b3d6ffec0608dcfaf18c5a69906d1490.jpeg","【AIGC Learning】Generate Prompts Using Word Graphs - Stable Diffusion Web UI Series 13","AI will become a powerful tool in education, transforming the way we learn and deliver instruction.  \n- Reid Hoffman","--",{"id":55,"publish_date":56,"is_original":4,"collection":57,"cover_url":58,"cover_url_1_1":59,"title":60,"summary":61,"author":28},413,"2023-09-08","#Neuroscience","article_res/cover/74f8302d78a23d9430f22171eae136b6.jpeg","article_res/cover/87ca08af81bb304746be5261160964c0.jpeg","Can machines be conscious?","Do we have an ethical obligation to not turn off conscious machines? Would turning them off be murder? No. I don't lose any sleep over unplugging a conscious machine.\n- Jeff Hawkins, \"A Thousand Brains\"",{"id":63,"publish_date":64,"is_original":23,"collection":65,"cover_url":66,"cover_url_1_1":67,"title":68,"summary":69,"author":28},178,"2024-09-09","#Entrepreneurship","article_res/cover/a7224f025b55d1820408085faef63079.jpeg","article_res/cover/11a9995b096cbf64465ef01b8673b154.jpeg","37signals company","This damn sense of relaxation",{"id":71,"publish_date":72,"is_original":4,"collection":73,"cover_url":74,"cover_url_1_1":75,"title":76,"summary":77,"author":78},460,"2023-05-12","#Google","article_res/cover/b970687b12faa52da976f91248c2aa7b.jpeg","article_res/cover/d1e71b52cfd2c63bc6e71f3e85ff135c.jpeg","Learn what BRC-20 and Ordinals are using Google Bard","Ordinals - a new protocol that allows users to store arbitrary data on the Bitcoin blockchain","Google Bard mainly writes",{"id":80,"publish_date":81,"is_original":23,"collection":5,"cover_url":82,"cover_url_1_1":83,"title":84,"summary":85,"author":28},309,"2024-03-26","article_res/cover/9877f95894ee88532d0e6012c23a2df3.jpeg","article_res/cover/20092164ddc109ce6ae56b1984246751.jpeg","Learning the Cancun Upgrade with lepton and perplexity","Building a quick conversation-based search demo with Lepton AI.",[87,95,103,111,119],{"id":88,"publish_date":89,"is_original":23,"collection":90,"cover_url":91,"cover_url_1_1":92,"title":93,"summary":94,"author":28},627,"2025-03-20","#AI Avatar #AI Video Generation","article_res/cover/d95481358f73924989f8c4ee9c75d1c8.jpeg","article_res/cover/b74bc0fab01f8b6a6aa87696c0c3ed8b.jpeg","DisPose: Generating Animated Videos by Driving Video with Reference Images","DisPose is a controllable human image animation method that enhances video generation.",{"id":96,"publish_date":97,"is_original":23,"collection":98,"cover_url":99,"cover_url_1_1":100,"title":101,"summary":102,"author":28},626,"2025-03-21","#Deep Dive into LLMs #LLM #RL #Andrej Karpathy #AlphaGo","article_res/cover/446553a5c8f8f2f07d97b20eaee84e56.jpeg","article_res/cover/e6c2823409c9b34624064b9acbaca6f1.jpeg","AlphaGo and the Power of Reinforcement Learning - Andrej Karpathy's Deep Dive on LLMs (Part 9)","Simply learning from humans will never surpass human capabilities.",{"id":104,"publish_date":105,"is_original":23,"collection":106,"cover_url":107,"cover_url_1_1":108,"title":109,"summary":110,"author":28},625,"2025-03-22","#Deep Dive into LLMs #LLM #RL #RLHF #Andrej Karpathy","article_res/cover/8da81d38b1e5cf558a164710fd8a5389.jpeg","article_res/cover/96f028d76c362a99a0dd56389e8f7a9b.jpeg","Reinforcement Learning from Human Feedback (RLHF) - Andrej Karpathy's Deep Dive on LLMs (Part 10)","Fine-Tuning Language Models from Human Preferences",{"id":112,"publish_date":113,"is_original":23,"collection":114,"cover_url":115,"cover_url_1_1":116,"title":117,"summary":118,"author":28},624,"2025-03-23","#Deep Dive into LLMs #LLM #Andrej Karpathy #AI Agent #MMM","article_res/cover/a5e7c3d48bb09109684d6513287c661d.jpeg","article_res/cover/d3f22b7c0ab8d82fd2da457a299e0773.jpeg","The Future of Large Language Models - Andrej Karpathy's In-Depth Explanation of LLM (Part 11)","preview of things to come",{"id":120,"publish_date":113,"is_original":23,"collection":121,"cover_url":122,"cover_url_1_1":123,"title":124,"summary":125,"author":28},623,"#Google #Voe #AI Video Generation","article_res/cover/c44062fea0f336c2b96b3928292392c2.jpeg","article_res/cover/a041041c69092ad3db191c5bf3ff981b.jpeg","Trial of Google's video generation model VOE2","Our state-of-the-art video generation model",[127,135,143],{"id":128,"publish_date":129,"is_original":23,"collection":130,"cover_url":131,"cover_url_1_1":132,"title":133,"summary":134,"author":28},300,"2024-04-16","#AI in Science #AGI","article_res/cover/6bf01e793e0f33e848572412eebdf9b0.jpeg","article_res/cover/91a5ee21dafecb914fabeb9430d46ec1.jpeg","Would Einstein lose his job - AI and Quantum Computing: A Glimpse into the Near Future","So Einstein's job is still safe.",{"id":136,"publish_date":137,"is_original":23,"collection":138,"cover_url":139,"cover_url_1_1":140,"title":141,"summary":142,"author":28},101,"2024-12-14","#Nvidia #AI 3D Generator","article_res/cover/693e07c85980c5c0c8fde3f037733f23.jpeg","article_res/cover/9ea8edff2d5d303ff3fffff3f6f9c3d9.jpeg","NVIDIA's open-source 3D project LLaMA-Mesh","LLaMA-Mesh: Unifying 3D Mesh Generation with Language Models",{"id":144,"publish_date":145,"is_original":23,"collection":146,"cover_url":147,"cover_url_1_1":148,"title":149,"summary":150,"author":28},131,"2024-11-10","#OpenAI","article_res/cover/87f8ed353ce39f31960e7cdfaf075a35.jpeg","article_res/cover/f597a63935f5cd32e484b4aadd6019e8.jpeg","ChatGPT has launched the Search function","Get fast, timely answers with links to relevant web sources.",{"big":152,"small":214},[153,181],{"title":154,"list":155},"AGENT",[156,157,165,173],{"id":112,"publish_date":113,"is_original":23,"collection":114,"cover_url":115,"cover_url_1_1":116,"title":117,"summary":118,"author":28},{"id":158,"publish_date":159,"is_original":23,"collection":160,"cover_url":161,"cover_url_1_1":162,"title":163,"summary":164,"author":28},622,"2025-03-24","#OWL #AI Agent #MAS #MCP #CUA","article_res/cover/cb50ca7f2bf4d1ed50202d7406e1c19a.jpeg","article_res/cover/4aa7aa3badfacf3cc84121334f1050dd.jpeg","OWL: Multi-agent collaboration","OWL: Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation",{"id":166,"publish_date":167,"is_original":23,"collection":168,"cover_url":169,"cover_url_1_1":170,"title":171,"summary":172,"author":28},620,"2025-03-26","#LLM #Google #Gemini #AI Agent","article_res/cover/53751a6dbbe990b1eb0b63f3b062aed4.jpeg","article_res/cover/031344981f0a212ff82d1f3a64aa5756.jpeg","Gemini 2.5 Pro, claimed to be far ahead of the competition, has been released with great fanfare: comprehensively surpassing other LLMs and topping the global rankings","Gemini 2.5: Our most intelligent AI model",{"id":174,"publish_date":175,"is_original":23,"collection":176,"cover_url":177,"cover_url_1_1":178,"title":179,"summary":180,"author":28},616,"2025-03-29","#MAS #AI Agent #AI Coder #MetaGPT #MGX","article_res/cover/9dcd702ad2035902e5e77967c34a1f1e.jpeg","article_res/cover/0a97fc4a922753c8f46ff38792020df8.jpeg","MGX - An automated website-building platform composed of multiple AI Agents","Your 24/7 AI Team | Dream, Chat, Create.",{"title":182,"list":183},"OPENAI",[184,191,199,206],{"id":185,"publish_date":167,"is_original":23,"collection":186,"cover_url":187,"cover_url_1_1":188,"title":189,"summary":190,"author":28},619,"#OpenAI #AI Image Generator #4o #MMM #AR Transformer","article_res/cover/2faffc97fcecf3151552cb0fd3206d89.jpeg","article_res/cover/1133cb4948af44cee2e7fbe79efb69e5.jpeg","The native image function of GPT-4o is officially launched","Introducing 4o Image Generation",{"id":192,"publish_date":193,"is_original":4,"collection":194,"cover_url":195,"cover_url_1_1":196,"title":197,"summary":198,"author":28},434,"2023-07-15","#Anthropic #OpenAI #Google #AI Code Generator #Claude","article_res/cover/e1b6f600a2b9f262a4392684e5f2ce25.jpeg","article_res/cover/6e1772e83f78f9a351ab23d3e414adee.jpeg","Latest Updates on Google Bard /Anthropic Claude2 / ChatGPT Code Interpreter","We want our models to use their programming skills to provide more natural interfaces to the basic functions of our computers.  \n - OpenAI",{"id":200,"publish_date":201,"is_original":4,"collection":146,"cover_url":202,"cover_url_1_1":203,"title":204,"summary":205,"author":28},417,"2023-08-24","article_res/cover/bccf897d50a88b18364e35f7466387e0.jpeg","article_res/cover/2f871085c1073717c1703ae86e18056f.jpeg","The GPT-3.5 Turbo fine-tuning (fine-tuning function) has been released～","Developers can now bring their own data to customize GPT-3.5 Turbo for their use cases.",{"id":207,"publish_date":208,"is_original":4,"collection":209,"cover_url":210,"cover_url_1_1":211,"title":212,"summary":213,"author":28},407,"2023-09-22","#OpenAI #AI Image Generator","article_res/cover/c59005e903d35cfc32346e2756e2728a.jpeg","article_res/cover/ba011d265e6d84b5c8cb6fd6b757b6cc.jpeg","Dall-E 3","DALL·E 3 understands significantly more nuance and detail, allowing you to easily translate your ideas into images.",[215,221,241],{"title":10,"list":216},[217,218,219,220],{"id":96,"publish_date":97,"is_original":23,"collection":98,"cover_url":99,"cover_url_1_1":100,"title":101,"summary":102,"author":28},{"id":104,"publish_date":105,"is_original":23,"collection":106,"cover_url":107,"cover_url_1_1":108,"title":109,"summary":110,"author":28},{"id":112,"publish_date":113,"is_original":23,"collection":114,"cover_url":115,"cover_url_1_1":116,"title":117,"summary":118,"author":28},{"id":166,"publish_date":167,"is_original":23,"collection":168,"cover_url":169,"cover_url_1_1":170,"title":171,"summary":172,"author":28},{"title":222,"list":223},"GOOGLE",[224,225,226,234],{"id":120,"publish_date":113,"is_original":23,"collection":121,"cover_url":122,"cover_url_1_1":123,"title":124,"summary":125,"author":28},{"id":166,"publish_date":167,"is_original":23,"collection":168,"cover_url":169,"cover_url_1_1":170,"title":171,"summary":172,"author":28},{"id":227,"publish_date":228,"is_original":23,"collection":229,"cover_url":230,"cover_url_1_1":231,"title":232,"summary":233,"author":28},615,"2025-03-30","#AI Researcher #AI Science #HKU #Google #AI Agent","article_res/cover/21fadf906067714bb0db31ae13a77c15.jpeg","article_res/cover/2697999a72bd26b22e85f0e92936d3ed.jpeg","AI-Researcher: LLM-driven全自动 scientific research assistant","AI-Researcher: Fully-Automated Scientific Discovery with LLM Agents  \nOpen-Sourced Alternative to Google AI Co-Scientist",{"id":235,"publish_date":236,"is_original":23,"collection":73,"cover_url":237,"cover_url_1_1":238,"title":239,"summary":240,"author":28},463,"2023-05-09","article_res/cover/89800f207723acdb55fc53bf999ebdc9.jpeg","article_res/cover/5764f369b4accd8f83e94aa4c077a175.jpeg","The Smallville sandbox world - A town with 25 virtual residents","Believable proxies of human behavior can empower interactive apps: Immersive environment, Rehearsal space, Prototyping tool",{"title":242,"list":243},"NVIDIA",[],true,{"code":4,"msg":5,"data":246},{"id":247,"publish_date":248,"is_original":23,"collection":249,"articles_id":250,"cover_url":251,"cover_url_1_1":252,"title":253,"summary":254,"author":28,"content":255,"popular":256,"list":317,"category":373,"tag":374},68,"2025-01-17","#LLM #MOE #AI Trader","0Wla-sRW6T8YRcypveZAig","article_res/cover/9732d16fb497c7a24974223ea6e03e0b.jpeg","article_res/cover/890d8fcba37de8c38fe5346c03c48b6f.jpeg","TradeExpert: AI Stock Trading with 50% Annualized Returns","TradExpert: Revolutionizing Trading with Mixture of Expert LLMs","\u003Cdiv class=\"rich_media_content js_underline_content\n                       autoTypeSetting24psection\n            \" id=\"js_content\">\u003Cp style='margin-bottom: 0px;cursor: pointer;color: rgb(0, 0, 0);font-size: 16px;line-height: 1.8em;letter-spacing: normal;text-align: left;padding-top: 8px;padding-bottom: 8px;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;background-color: rgb(255, 255, 255);'>今天看了一个 Paper：TradeExpert，https://arxiv.org/html/2411.00782v1\u003C/p>\u003Cp style='margin-bottom: 0px;cursor: pointer;color: rgb(0, 0, 0);font-size: 16px;line-height: 1.8em;letter-spacing: normal;text-align: left;padding-top: 8px;padding-bottom: 8px;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;background-color: rgb(255, 255, 255);'>TradeExpert提出了一种基于\u003Cstrong style=\"cursor: pointer;background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">专家混合模型（Mixture of Experts, MoE）\u003C/strong>的框架，将金融领域的四大数据源（新闻、市场数据、阿尔法因子和基本面数据）整合到四个专用LLMs中，每个模型分别解析其独特领域的数据。这些专用模型的输出通过一个“通用专家”模型进行整合，从而生成最终的预测或决策。此框架具有两种模式：\u003C/p>\u003Col style='margin-top: 8px;margin-bottom: 8px;cursor: pointer;padding-left: 25px;color: rgb(0, 0, 0);font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);' class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">预测模式\u003C/strong>：预测个股价格波动。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">排序模式\u003C/strong>：用于量化投资策略中的选股排序。\u003C/section>\u003C/li>\u003C/ol>\u003Cp style=\"text-align: center;\">\u003Cimg class=\"rich_pages wxw-img js_insertlocalimg\" data-imgfileid=\"100009299\" data-ratio=\"0.43333333333333335\" data-s=\"300,640\" data-type=\"png\" data-w=\"1080\" style=\"\" src=\"./assets/17423771965610.6551218143193966.png\">\u003C/p>\u003Ch3 style='margin-top: 30px;margin-bottom: 15px;color: rgba(0, 0, 0, 0.85);cursor: pointer;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);'>\u003Cspan style=\"cursor: pointer;font-size: 20px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;font-weight: bold;display: block;\">对比示意图\u003C/span>\u003C/h3>\u003Cp style='margin-bottom: 0px;cursor: pointer;color: rgb(0, 0, 0);font-size: 16px;line-height: 1.8em;letter-spacing: normal;text-align: left;padding-top: 8px;padding-bottom: 8px;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;background-color: rgb(255, 255, 255);'>传统金融模型、基于LLM的金融模型以及基于MoE LLM的金融模型之间的差异。\u003C/p>\u003Cp style=\"text-align: center;\">\u003Cimg class=\"rich_pages wxw-img js_insertlocalimg\" data-imgfileid=\"100009300\" data-ratio=\"0.4040632054176072\" data-s=\"300,640\" data-type=\"png\" data-w=\"886\" style=\"\" src=\"./assets/17423771966620.6967017069973904.png\">\u003C/p>\u003Ch3 style='margin-top: 30px;margin-bottom: 15px;color: rgba(0, 0, 0, 0.85);cursor: pointer;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);'>\u003Cspan style=\"cursor: pointer;font-size: 20px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;font-weight: bold;display: block;\">关键优势\u003C/span>\u003C/h3>\u003Col style='margin-top: 8px;margin-bottom: 8px;cursor: pointer;padding-left: 25px;color: rgb(0, 0, 0);font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);' class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">多模态数据整合\u003C/strong>：通过专用模型同时分析结构化数据（如市场指标）和非结构化数据（如新闻文本），克服了传统金融模型对数据源整合的局限性。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">灵活性与拓展性\u003C/strong>：在不同市场情景中，该框架表现出超越传统基准的性能。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">新数据集发布\u003C/strong>：研究还附带了一个大规模金融数据集，为模型的广泛验证提供了基础。\u003C/section>\u003C/li>\u003C/ol>\u003Ch3 style='margin-top: 30px;margin-bottom: 15px;color: rgba(0, 0, 0, 0.85);cursor: pointer;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);'>\u003Cspan style=\"cursor: pointer;font-size: 20px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;font-weight: bold;display: block;\">系统的实用价值\u003C/span>\u003C/h3>\u003Cp style='margin-bottom: 0px;cursor: pointer;color: rgb(0, 0, 0);font-size: 16px;line-height: 1.8em;letter-spacing: normal;text-align: left;padding-top: 8px;padding-bottom: 8px;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;background-color: rgb(255, 255, 255);'>以年化50%的投资回报为背景，TradeExpert的成功与其以下特点密切相关：\u003C/p>\u003Col style='margin-top: 8px;margin-bottom: 8px;cursor: pointer;padding-left: 25px;color: rgb(0, 0, 0);font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);' class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">高效利用LLMs\u003C/strong>：专门优化的语言模型能够从市场噪声中提取有效信号，辅助投资决策。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">提升预测准确率\u003C/strong>：通过引入专用模型和通用整合机制，增强了对市场趋势的捕捉能力。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">量化投资工具的集成\u003C/strong>：能直接用于选股排序，支持自动化的量化交易策略。\u003C/section>\u003C/li>\u003C/ol>\u003Ch3 style='margin-top: 30px;margin-bottom: 15px;color: rgba(0, 0, 0, 0.85);cursor: pointer;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);'>\u003Cspan style=\"cursor: pointer;font-size: 20px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;font-weight: bold;display: block;\">合作机构\u003C/span>\u003C/h3>\u003Col style='margin-top: 8px;margin-bottom: 8px;cursor: pointer;padding-left: 25px;color: rgb(0, 0, 0);font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);' class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cp style=\"cursor: pointer;color: rgb(0, 0, 0);line-height: 1.8em;letter-spacing: 0em;text-indent: 0em;padding-top: 8px;padding-bottom: 8px;\">\u003Cstrong style=\"cursor: pointer;background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">DIRO (Department of Computer Science and Operations Research), Université de Montréal\u003C/strong>\u003C/p>\u003C/section>\u003C/li>\u003C/ol>\u003Cul style=\"margin-top: 8px;margin-bottom: 8px;cursor: pointer;list-style-type: disc;padding-left: 25px;color: rgb(0, 0, 0);\" class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">加拿大蒙特利尔大学的计算机科学与运筹学系，专注于人工智能、优化和计算领域的研究。\u003C/section>\u003C/li>\u003C/ul>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cp style=\"cursor: pointer;color: rgb(0, 0, 0);line-height: 1.8em;letter-spacing: 0em;text-indent: 0em;padding-top: 8px;padding-bottom: 8px;\">\u003Cstrong style=\"cursor: pointer;background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">Institut Courtois, Université de Montréal\u003C/strong>\u003C/p>\u003C/section>\u003C/li>\u003Cul style=\"margin-top: 8px;margin-bottom: 8px;cursor: pointer;list-style-type: disc;padding-left: 25px;color: rgb(0, 0, 0);\" class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">蒙特利尔大学的Courtois研究所，支持跨学科研究，尤其在人工智能与自然科学交叉领域。\u003C/section>\u003C/li>\u003C/ul>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cp style=\"cursor: pointer;color: rgb(0, 0, 0);line-height: 1.8em;letter-spacing: 0em;text-indent: 0em;padding-top: 8px;padding-bottom: 8px;\">\u003Cstrong style=\"cursor: pointer;background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">Mila - Quebec AI Institute\u003C/strong>\u003C/p>\u003C/section>\u003C/li>\u003Cul style=\"margin-top: 8px;margin-bottom: 8px;cursor: pointer;list-style-type: disc;padding-left: 25px;color: rgb(0, 0, 0);\" class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">加拿大魁北克人工智能研究所（Mila），是世界领先的人工智能研究中心之一，聚焦深度学习、强化学习等前沿技术。\u003C/section>\u003C/li>\u003C/ul>\u003Ch3 style='margin-top: 30px;margin-bottom: 15px;color: rgba(0, 0, 0, 0.85);cursor: pointer;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);'>\u003Cspan style=\"cursor: pointer;font-size: 20px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;font-weight: bold;display: block;\">数据集\u003C/span>\u003C/h3>\u003Cp style='margin-bottom: 0px;cursor: pointer;color: rgb(0, 0, 0);font-size: 16px;line-height: 1.8em;letter-spacing: normal;text-align: left;padding-top: 8px;padding-bottom: 8px;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;background-color: rgb(255, 255, 255);'>本研究收集了一个综合数据集，涵盖了以下四个主要数据来源，时间跨度为\u003Cstrong style=\"cursor: pointer;background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">2020年1月1日\u003C/strong>至\u003Cstrong style=\"cursor: pointer;background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">2023年12月31日\u003C/strong>，共计四年：\u003C/p>\u003Col style='margin-top: 8px;margin-bottom: 8px;cursor: pointer;padding-left: 25px;color: rgb(0, 0, 0);font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);' class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cp style=\"cursor: pointer;color: rgb(0, 0, 0);line-height: 1.8em;letter-spacing: 0em;text-indent: 0em;padding-top: 8px;padding-bottom: 8px;\">\u003Cstrong style=\"cursor: pointer;background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">新闻\u003C/strong>：来自新闻文章的文本信息，涵盖与股票和市场状况相关的内容。\u003C/p>\u003C/section>\u003C/li>\u003C/ol>\u003Cul style=\"margin-top: 8px;margin-bottom: 8px;cursor: pointer;list-style-type: disc;padding-left: 25px;color: rgb(0, 0, 0);\" class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">来源：包括\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">Yahoo Finance\u003C/strong>、\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">Reuters\u003C/strong>、\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">InvestorPlace\u003C/strong>、\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">GlobeNewswire\u003C/strong>、\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">The Motley Fool\u003C/strong>等权威财经新闻源。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">数据量：共计\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">524,995篇\u003C/strong>与\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">S&P 500\u003C/strong>股票相关的新闻文章。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">平均字数：每篇文章约\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">596.4字\u003C/strong>。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">每篇新闻关联一组相关股票代码（tickers）。\u003C/section>\u003C/li>\u003C/ul>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cp style=\"cursor: pointer;color: rgb(0, 0, 0);line-height: 1.8em;letter-spacing: 0em;text-indent: 0em;padding-top: 8px;padding-bottom: 8px;\">\u003Cstrong style=\"cursor: pointer;background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">市场数据\u003C/strong>：股票交易活动的历史数据，包括\u003Cstrong style=\"cursor: pointer;background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">开盘价（Open）、最高价（High）、最低价（Low）、收盘价（Close）、交易量（Volume）\u003C/strong>。\u003C/p>\u003C/section>\u003C/li>\u003Cul style=\"margin-top: 8px;margin-bottom: 8px;cursor: pointer;list-style-type: disc;padding-left: 25px;color: rgb(0, 0, 0);\" class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">内容：\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">S&P 500\u003C/strong>股票的每日历史\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">OHLCV（开盘价、最高价、最低价、收盘价、交易量）\u003C/strong>记录。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">数据量：共计\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">481,484条记录\u003C/strong>，提供了指定期间内股票交易活动的详细视图。\u003C/section>\u003C/li>\u003C/ul>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cp style=\"cursor: pointer;color: rgb(0, 0, 0);line-height: 1.8em;letter-spacing: 0em;text-indent: 0em;padding-top: 8px;padding-bottom: 8px;\">\u003Cstrong style=\"cursor: pointer;background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">阿尔法因子\u003C/strong>：具有预测股票价格变动能力的定量指标和信号。\u003C/p>\u003C/section>\u003C/li>\u003Cul style=\"margin-top: 8px;margin-bottom: 8px;cursor: pointer;list-style-type: disc;padding-left: 25px;color: rgb(0, 0, 0);\" class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">内容：包含\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">108个技术指标和因子\u003C/strong>，以及它们的表达式，这些因子被认为对股票价格走势具有预测能力。\u003C/section>\u003C/li>\u003C/ul>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cp style=\"cursor: pointer;color: rgb(0, 0, 0);line-height: 1.8em;letter-spacing: 0em;text-indent: 0em;padding-top: 8px;padding-bottom: 8px;\">\u003Cstrong style=\"cursor: pointer;background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">基本面数据\u003C/strong>：公司财务健康和经营表现的反映，包括\u003Cstrong style=\"cursor: pointer;background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">财报电话会议记录\u003C/strong>和\u003Cstrong style=\"cursor: pointer;background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">基本财务指标\u003C/strong>。\u003C/p>\u003C/section>\u003C/li>\u003Cul style=\"margin-top: 8px;margin-bottom: 8px;cursor: pointer;list-style-type: disc;padding-left: 25px;color: rgb(0, 0, 0);\" class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">财报电话会议记录\u003C/strong>：来源于\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">Seeking Alpha\u003C/strong>，每只股票在四年内提供了16次季度更新的记录。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">财务指标\u003C/strong>：包括\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">每股收益（EPS）\u003C/strong>、\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">市盈率（P/E Ratio）\u003C/strong>、\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">每股账面价值（BVPS）\u003C/strong>等。\u003C/section>\u003C/li>\u003C/ul>\u003Ch3 style='margin-top: 30px;margin-bottom: 15px;color: rgba(0, 0, 0, 0.85);cursor: pointer;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);'>\u003Cspan style=\"cursor: pointer;font-size: 20px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;font-weight: bold;display: block;\">TradExpert 框架\u003C/span>\u003C/h3>\u003Col style='margin-top: 8px;margin-bottom: 8px;cursor: pointer;padding-left: 25px;color: rgb(0, 0, 0);font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);' class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cp style=\"cursor: pointer;color: rgb(0, 0, 0);line-height: 1.8em;letter-spacing: 0em;text-indent: 0em;padding-top: 8px;padding-bottom: 8px;\">\u003Cstrong style=\"cursor: pointer;background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">专家LLM架构\u003C/strong>：\u003C/p>\u003C/section>\u003C/li>\u003C/ol>\u003Cul style=\"margin-top: 8px;margin-bottom: 8px;cursor: pointer;list-style-type: disc;padding-left: 25px;color: rgb(0, 0, 0);\" class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">所有专家LLM均基于\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">LLaMA-2-7B\u003C/strong>骨干模型（Touvron et al. 2023b）。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">通过\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">LoRA（低秩自适应微调）机制\u003C/strong>（Hu et al. 2022）进行监督微调。\u003C/section>\u003C/li>\u003C/ul>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cp style=\"cursor: pointer;color: rgb(0, 0, 0);line-height: 1.8em;letter-spacing: 0em;text-indent: 0em;padding-top: 8px;padding-bottom: 8px;\">\u003Cstrong style=\"cursor: pointer;background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">数据预处理\u003C/strong>：\u003C/p>\u003C/section>\u003C/li>\u003Cul style=\"margin-top: 8px;margin-bottom: 8px;cursor: pointer;list-style-type: disc;padding-left: 25px;color: rgb(0, 0, 0);\" class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">在训练和微调之前，对原始数据集进行预处理，构建适合每个LLM的\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">提示（prompts）\u003C/strong>、\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">指令（instructions）\u003C/strong>和\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">真实响应（ground-truth responses）\u003C/strong>。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">表1展示了预处理数据集的整体描述。\u003C/section>\u003C/li>\u003C/ul>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cp style=\"cursor: pointer;color: rgb(0, 0, 0);line-height: 1.8em;letter-spacing: 0em;text-indent: 0em;padding-top: 8px;padding-bottom: 8px;\">\u003Cstrong style=\"cursor: pointer;background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">管道描述\u003C/strong>：\u003C/p>\u003C/section>\u003C/li>\u003Cul style=\"margin-top: 8px;margin-bottom: 8px;cursor: pointer;list-style-type: disc;padding-left: 25px;color: rgb(0, 0, 0);\" class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">四个专家LLM\u003C/strong>分别专注于处理新闻数据、市场数据、阿尔法因子和基本面数据。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">通用专家LLM\u003C/strong>负责整合四个专家生成的摘要，以形成最终的股票预测或排序输出。\u003C/section>\u003C/li>\u003C/ul>\u003Ch3 style='margin-top: 30px;margin-bottom: 15px;color: rgba(0, 0, 0, 0.85);cursor: pointer;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);'>\u003Cspan style=\"cursor: pointer;font-size: 20px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;font-weight: bold;display: block;\">方法详述\u003C/span>\u003C/h3>\u003Ch4 style='margin-top: 30px;margin-bottom: 15px;color: rgba(0, 0, 0, 0.85);cursor: pointer;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);'>\u003Cspan style=\"cursor: pointer;font-size: 18px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;font-weight: bold;display: block;\">1. \u003Cstrong style=\"cursor: pointer;background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">新闻分析专家（News Analyst）\u003C/strong>\u003C/span>\u003C/h4>\u003Cul style='margin-top: 8px;margin-bottom: 8px;cursor: pointer;padding-left: 25px;color: rgb(0, 0, 0);font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);' class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">功能\u003C/strong>：分析新闻文章文本，预测股票走势。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">实现方式\u003C/strong>：\u003C/section>\u003C/li>\u003Cul style=\"margin-top: 8px;margin-bottom: 8px;cursor: pointer;list-style-type: square;padding-left: 25px;color: rgb(0, 0, 0);\" class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">使用\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">思维链推理（CoT）\u003C/strong>方法，提供股票走势预测和新闻与预测的关联推理。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">真实推理数据\u003C/strong>：通过OpenAI GPT-4 API预生成，结合实际股票走势与新闻内容。\u003Cspan style=\"letter-spacing: 0em;\">\u003C/span>\u003C/section>\u003C/li>\u003C/ul>\u003C/ul>\u003Csection style='cursor: pointer;margin-top: 20px;margin-bottom: 20px;padding: 10px 20px;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;background: none 0% 0% / auto no-repeat scroll padding-box border-box rgb(250, 250, 250);width: auto;height: auto;box-shadow: rgba(0, 0, 0, 0) 0px 0px 0px 0px;color: rgb(0, 0, 0);font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;letter-spacing: normal;text-align: left;'>\u003Csection style=\"cursor: pointer;\">\u003Cp style=\"cursor: pointer;line-height: 1.8em;letter-spacing: 0em;text-indent: 0em;padding-top: 8px;padding-bottom: 8px;\">\u003Cstrong>Instruction\u003C/strong>: You are provided with a news article. Please predict how the stock will perform in the next \u003Cd style=\"cursor: pointer;\">days. Your response should include your reasoning followed by a prediction of ”Rise” or ”Fall” in the specified format. Format your response as follows: Reasoning: [Your reasoning here] Prediction: [Rise or Fall]\u003C/d>\u003C/p>\u003Cp style=\"cursor: pointer;line-height: 1.8em;letter-spacing: 0em;text-indent: 0em;padding-top: 8px;padding-bottom: 8px;\">\u003Cd style=\"cursor: pointer;\">\u003Cstrong>Prompt\u003C/strong>: News Article: [Insert news article text here] Question: Given the information in the news article above, how is the stock expected to perform in the next \u003Cd style=\"cursor: pointer;\">days?\u003C/d>\u003C/d>\u003C/p>\u003C/section>\u003C/section>\u003Ch4 style='margin-top: 30px;margin-bottom: 15px;color: rgba(0, 0, 0, 0.85);cursor: pointer;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);'>\u003Cspan style=\"cursor: pointer;font-size: 18px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;font-weight: bold;display: block;\">2. \u003Cstrong style=\"cursor: pointer;background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">市场分析专家（Market Analyst）\u003C/strong>\u003C/span>\u003C/h4>\u003Cul style='margin-top: 8px;margin-bottom: 8px;cursor: pointer;padding-left: 25px;color: rgb(0, 0, 0);font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);' class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">功能\u003C/strong>：分析历史\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">OHLCV\u003C/strong>数据，预测股票走势。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">关键技术\u003C/strong>：\u003C/section>\u003C/li>\u003Cul style=\"margin-top: 8px;margin-bottom: 8px;cursor: pointer;list-style-type: square;padding-left: 25px;color: rgb(0, 0, 0);\" class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">时间序列数据通过分块嵌入转换为小片段表示。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">通过多头注意力机制和文本原型重新编程为嵌入。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">时间序列数据被重新编程为文本表示，以解决LLM与连续时间序列数据不兼容的问题。\u003Cspan style=\"letter-spacing: 0em;\">\u003C/span>\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">最终将嵌入与由TSFresh提取的统计信息描述结合，作为输入提示。\u003C/section>\u003C/li>\u003C/ul>\u003C/ul>\u003Csection style='cursor: pointer;margin-top: 20px;margin-bottom: 20px;padding: 10px 20px;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;background: none 0% 0% / auto no-repeat scroll padding-box border-box rgb(250, 250, 250);width: auto;height: auto;box-shadow: rgba(0, 0, 0, 0) 0px 0px 0px 0px;color: rgb(0, 0, 0);font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;letter-spacing: normal;text-align: left;'>\u003Csection style=\"cursor: pointer;\">\u003Cp style=\"cursor: pointer;line-height: 1.8em;letter-spacing: 0em;text-indent: 0em;padding-top: 8px;padding-bottom: 8px;\">\u003Cstrong>Instruction\u003C/strong>: You are provided with historical OHLCV data of the past 20 days and a description of its statistics. Please predict how the stock will perform the next \u003Cd style=\"cursor: pointer;\">day. Your response should be “Rise” or ”Fall”.\u003C/d>\u003C/p>\u003Cp style=\"cursor: pointer;line-height: 1.8em;letter-spacing: 0em;text-indent: 0em;padding-top: 8px;padding-bottom: 8px;\">\u003Cd style=\"cursor: pointer;\">\u003Cstrong>Prompt\u003C/strong>: \u003Cembbedings of=\"\" reprogrammed=\"\" ohlcv=\"\" style=\"cursor: pointer;\">Statistics: The historical prices have a minimum close of \u003Cmin val=\"\" style=\"cursor: pointer;\">\u003Cmin d=\"\" style=\"cursor: pointer;\">days ago, a maximum close of \u003Cmax val=\"\" style=\"cursor: pointer;\">\u003Cmax d=\"\" style=\"cursor: pointer;\">days ago, and a median close of \u003Cmedian val=\"\" style=\"cursor: pointer;\">\u003Cmedian d=\"\" style=\"cursor: pointer;\">days ago. The overall trend is \u003Cupward or=\"\" downward=\"\" style=\"cursor: pointer;\">... Question: Given the reprogrammed OHLCV data and its statistics, how is the stock expected to perform in the next \u003Cd style=\"cursor: pointer;\">days?\u003C/d>\u003C/upward>\u003C/median>\u003C/median>\u003C/max>\u003C/max>\u003C/min>\u003C/min>\u003C/embbedings>\u003C/d>\u003C/p>\u003C/section>\u003C/section>\u003Ch4 style='margin-top: 30px;margin-bottom: 15px;color: rgba(0, 0, 0, 0.85);cursor: pointer;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);'>\u003Cspan style=\"cursor: pointer;font-size: 18px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;font-weight: bold;display: block;\">3. \u003Cstrong style=\"cursor: pointer;background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">阿尔法因子专家（Alpha Expert）\u003C/strong>\u003C/span>\u003C/h4>\u003Cul style='margin-top: 8px;margin-bottom: 8px;cursor: pointer;padding-left: 25px;color: rgb(0, 0, 0);font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);' class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">功能\u003C/strong>：处理基于表达式的阿尔法因子，分析股票走势。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">实现方式\u003C/strong>：\u003C/section>\u003C/li>\u003Cul style=\"margin-top: 8px;margin-bottom: 8px;cursor: pointer;list-style-type: square;padding-left: 25px;color: rgb(0, 0, 0);\" class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">使用GPT-4生成因子表达式的自然语言描述。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">每只股票的阿尔法因子通过OHLCV数据计算综合得分，并基于LightGBM模型选择\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">Top-K因子\u003C/strong>。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">输入提示包括阿尔法因子的描述及计算值。\u003C/section>\u003C/li>\u003C/ul>\u003C/ul>\u003Ch4 style='margin-top: 30px;margin-bottom: 15px;color: rgba(0, 0, 0, 0.85);cursor: pointer;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);'>\u003Cspan style=\"cursor: pointer;font-size: 18px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;font-weight: bold;display: block;\">4. \u003Cstrong style=\"cursor: pointer;background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">基本面分析专家（Fundamental Analyst）\u003C/strong>\u003C/span>\u003C/h4>\u003Cul style='margin-top: 8px;margin-bottom: 8px;cursor: pointer;padding-left: 25px;color: rgb(0, 0, 0);font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);' class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">功能\u003C/strong>：分析基本面数据（如财报电话会议记录与财务指标），按季度预测股票价格走势。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">实现方式\u003C/strong>：\u003C/section>\u003C/li>\u003Cul style=\"margin-top: 8px;margin-bottom: 8px;cursor: pointer;list-style-type: square;padding-left: 25px;color: rgb(0, 0, 0);\" class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">微调过程类似于新闻分析专家。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">输出包括以下五种分类的预测结果：\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">“大幅上涨”\u003C/strong>、\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">“小幅上涨”\u003C/strong>、\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">“无变化”\u003C/strong>、\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">“小幅下跌”\u003C/strong>、\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">“大幅下跌”\u003C/strong>，并附加推理说明。\u003C/section>\u003C/li>\u003C/ul>\u003C/ul>\u003Ch4 style='margin-top: 30px;margin-bottom: 15px;color: rgba(0, 0, 0, 0.85);cursor: pointer;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);'>\u003Cspan style=\"cursor: pointer;font-size: 18px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;font-weight: bold;display: block;\">5. \u003Cstrong style=\"cursor: pointer;background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">通用专家（General Expert）\u003C/strong>\u003C/span>\u003C/h4>\u003Cul style='margin-top: 8px;margin-bottom: 8px;cursor: pointer;padding-left: 25px;color: rgb(0, 0, 0);font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);' class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">功能\u003C/strong>：总结四个专用专家的报告，执行以下两种模式：\u003C/section>\u003C/li>\u003Cul style=\"margin-top: 8px;margin-bottom: 8px;cursor: pointer;list-style-type: square;padding-left: 25px;color: rgb(0, 0, 0);\" class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">预测模式\u003C/strong>：用于股票走势预测，输出二元结果（涨/跌）。\u003C/section>\u003C/li>\u003C/ul>\u003C/ul>\u003Csection style='cursor: pointer;margin-top: 20px;margin-bottom: 20px;padding: 10px 20px;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;background: none 0% 0% / auto no-repeat scroll padding-box border-box rgb(250, 250, 250);width: auto;height: auto;box-shadow: rgba(0, 0, 0, 0) 0px 0px 0px 0px;color: rgb(0, 0, 0);font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;letter-spacing: normal;text-align: left;'>\u003Csection style=\"cursor: pointer;\">\u003Cp style=\"cursor: pointer;line-height: 1.8em;letter-spacing: 0em;text-indent: 0em;padding-top: 8px;padding-bottom: 8px;\">\u003Cstrong>Instruction\u003C/strong>: You are provided with a summarized report of the stock. Please predict whether the stock will rise or fall the next \u003Cd style=\"cursor: pointer;\">day. Format your response as follows: Reasoning: [Your reasoning here] Prediction: [Rise or Fall].\u003C/d>\u003C/p>\u003Cp style=\"cursor: pointer;line-height: 1.8em;letter-spacing: 0em;text-indent: 0em;padding-top: 8px;padding-bottom: 8px;\">\u003Cd style=\"cursor: pointer;\">\u003Cstrong>Prompt\u003C/strong>: Summarized Report: [Insert summarized report here] Question: Based on the summarized report, will the stock rise or fall in the next < D > days?\u003C/d>\u003C/p>\u003C/section>\u003C/section>\u003Cul style='margin-top: 8px;margin-bottom: 8px;cursor: pointer;padding-left: 25px;color: rgb(0, 0, 0);font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);' class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cp style=\"cursor: pointer;color: rgb(0, 0, 0);line-height: 1.8em;letter-spacing: 0em;text-indent: 0em;padding-top: 8px;padding-bottom: 8px;\">\u003Cstrong style=\"cursor: pointer;background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">排序模式\u003C/strong>：用于股票交易，比较两只股票的表现优劣。\u003C/p>\u003C/section>\u003C/li>\u003Cul style=\"margin-top: 8px;margin-bottom: 8px;cursor: pointer;list-style-type: square;padding-left: 25px;color: rgb(0, 0, 0);\" class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">采用基于松弛比较的排序算法（类似冒泡排序），对股票进行\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">Top-K\u003C/strong>排名。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">尽管其他排序算法具有更高效率，但由于LLM比较器的非传递性，较多的比较次数通常能带来更准确的排序结果。\u003C/section>\u003C/li>\u003C/ul>\u003C/ul>\u003Csection style='cursor: pointer;margin-top: 20px;margin-bottom: 20px;padding: 10px 20px;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;background: none 0% 0% / auto no-repeat scroll padding-box border-box rgb(250, 250, 250);width: auto;height: auto;box-shadow: rgba(0, 0, 0, 0) 0px 0px 0px 0px;color: rgb(0, 0, 0);font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;letter-spacing: normal;text-align: left;'>\u003Csection style=\"cursor: pointer;\">\u003Cp style=\"cursor: pointer;line-height: 1.8em;letter-spacing: 0em;text-indent: 0em;padding-top: 8px;padding-bottom: 8px;\">\u003Cstrong>Instruction\u003C/strong>: You are provided with summarized reports of two stocks. Please determine which stock will perform better the next \u003Cd style=\"cursor: pointer;\">day. Please output Stock AAA or Stock BBB.\u003C/d>\u003C/p>\u003Cp style=\"cursor: pointer;line-height: 1.8em;letter-spacing: 0em;text-indent: 0em;padding-top: 8px;padding-bottom: 8px;\">\u003Cd style=\"cursor: pointer;\">\u003Cstrong>Prompt\u003C/strong>: Summarized Report for Stock AAA: [Report A] Summarized Report for Stock BBB: [Report B] Question: Based on the summarized reports, which stock will perform better in the next < D > days?\u003C/d>\u003C/p>\u003C/section>\u003C/section>\u003Cul style='margin-top: 8px;margin-bottom: 8px;cursor: pointer;padding-left: 25px;color: rgb(0, 0, 0);font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);' class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">微调任务\u003C/strong>：通用专家针对股票走势预测和股票比较两个任务同时进行微调。\u003C/section>\u003C/li>\u003C/ul>\u003Ch3 style='margin-top: 30px;margin-bottom: 15px;color: rgba(0, 0, 0, 0.85);cursor: pointer;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);'>\u003Cspan style=\"cursor: pointer;font-size: 20px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;font-weight: bold;display: block;\">结果\u003C/span>\u003C/h3>\u003Ch4 style='margin-top: 30px;margin-bottom: 15px;color: rgba(0, 0, 0, 0.85);cursor: pointer;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);'>\u003Cspan style=\"cursor: pointer;font-size: 18px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;font-weight: bold;display: block;\">股票走势预测（Stock Movement Prediction）\u003C/span>\u003C/h4>\u003Col style='margin-top: 8px;margin-bottom: 8px;cursor: pointer;padding-left: 25px;color: rgb(0, 0, 0);font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);' class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cp style=\"cursor: pointer;color: rgb(0, 0, 0);line-height: 1.8em;letter-spacing: 0em;text-indent: 0em;padding-top: 8px;padding-bottom: 8px;\">\u003Cstrong style=\"cursor: pointer;background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">实验设置\u003C/strong>：\u003C/p>\u003C/section>\u003C/li>\u003C/ol>\u003Cul style=\"margin-top: 8px;margin-bottom: 8px;cursor: pointer;list-style-type: disc;padding-left: 25px;color: rgb(0, 0, 0);\" class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">复现了所有基线模型或利用开源代码（SLOT除外，使用相关论文中的结果）。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">为了公平对比，仅在\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">TradExpert\u003C/strong>中包含\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">News Analyst\u003C/strong>和\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">Market Analyst\u003C/strong>模块，命名为\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">TradExpert-NM\u003C/strong>。\u003C/section>\u003C/li>\u003C/ul>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cp style=\"cursor: pointer;color: rgb(0, 0, 0);line-height: 1.8em;letter-spacing: 0em;text-indent: 0em;padding-top: 8px;padding-bottom: 8px;\">\u003Cstrong style=\"cursor: pointer;background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">结果概览\u003C/strong>：\u003C/p>\u003C/section>\u003Cp style=\"text-align: center;\">\u003Cimg class=\"rich_pages wxw-img js_insertlocalimg\" data-imgfileid=\"100009301\" data-ratio=\"0.6240740740740741\" data-s=\"300,640\" data-type=\"png\" data-w=\"1080\" style=\"\" src=\"./assets/17423771965620.6190333936209467.png\">\u003C/p>\u003C/li>\u003Cul style=\"margin-top: 8px;margin-bottom: 8px;cursor: pointer;list-style-type: disc;padding-left: 25px;color: rgb(0, 0, 0);\" class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">ACL18、BigData22、CIKM18数据集以推文为主，文本较短。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">S&P500数据集由新闻文章组成，文本更长，因此TradExpert-NM在该数据集上的提升尤为显著。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">混合模型\u003C/strong>：SLOT在ACL18数据集上表现出色，特别是在准确率和MCC指标上，得益于其提出的全球市场指导机制。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">LLMs\u003C/strong>：InternLM在自有的S&P500数据集上表现优异。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">TradExpert-NM\u003C/strong>：基于专家混合LLM方法，表现优于其他模型，在所有数据集上均实现了最优性能（ACL18的MCC除外）。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">数据特点\u003C/strong>：\u003C/section>\u003C/li>\u003C/ul>\u003Ch4 style='margin-top: 30px;margin-bottom: 15px;color: rgba(0, 0, 0, 0.85);cursor: pointer;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);'>\u003Cspan style=\"cursor: pointer;font-size: 18px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;font-weight: bold;display: block;\">股票交易模拟（Stock Trading Simulation）\u003C/span>\u003C/h4>\u003Col style='margin-top: 8px;margin-bottom: 8px;cursor: pointer;padding-left: 25px;color: rgb(0, 0, 0);font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);' class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cp style=\"cursor: pointer;color: rgb(0, 0, 0);line-height: 1.8em;letter-spacing: 0em;text-indent: 0em;padding-top: 8px;padding-bottom: 8px;\">\u003Cstrong style=\"cursor: pointer;background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">实验设置\u003C/strong>：\u003C/p>\u003C/section>\u003C/li>\u003C/ol>\u003Cul style=\"margin-top: 8px;margin-bottom: 8px;cursor: pointer;list-style-type: disc;padding-left: 25px;color: rgb(0, 0, 0);\" class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">回测使用了DOW 30（道琼斯30种成分股）作为股票池，是S&P500的子集。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">TradExpert采用Top-K排序股票的“买入并持有”策略。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">回测时间段与测试集一致：\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">2023年1月1日至2023年12月31日\u003C/strong>。\u003C/section>\u003C/li>\u003C/ul>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cp style=\"cursor: pointer;color: rgb(0, 0, 0);line-height: 1.8em;letter-spacing: 0em;text-indent: 0em;padding-top: 8px;padding-bottom: 8px;\">\u003Cstrong style=\"cursor: pointer;background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">结果概览\u003C/strong>：\u003C/p>\u003C/section>\u003Cp style=\"text-align: center;\">\u003Cimg class=\"rich_pages wxw-img js_insertlocalimg\" data-imgfileid=\"100009302\" data-ratio=\"1.092071611253197\" data-s=\"300,640\" data-type=\"png\" data-w=\"782\" style=\"width: 325px;height: 355px;\" src=\"./assets/17423771965660.9444648958861388.png\">\u003C/p>\u003C/li>\u003Cul style=\"margin-top: 8px;margin-bottom: 8px;cursor: pointer;list-style-type: disc;padding-left: 25px;color: rgb(0, 0, 0);\" class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">以\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">49.79%的年化收益率（AR）\u003C/strong>和\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">9.95%的波动率（AV）\u003C/strong>显著领先。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">夏普比率（5.01）\u003C/strong>显示出每单位风险对应的回报非常高。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">传统模型\u003C/strong>：XGBoost表现较好，收益率较高，但波动率和最大回撤也较高，风险较大。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">深度学习模型\u003C/strong>：整体优于传统模型，其中DeepTrader收益率和夏普比率最高。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">TradExpert\u003C/strong>\u003Cspan style=\"letter-spacing: 0em;\">显现出一致的高收益优势。\u003C/span>\u003C/section>\u003Cp style=\"text-align: center;\">\u003Cimg class=\"rich_pages wxw-img js_insertlocalimg\" data-imgfileid=\"100009307\" data-ratio=\"0.6425925925925926\" data-s=\"300,640\" data-type=\"png\" data-w=\"1080\" style=\"width: 454px;height: 292px;\" src=\"./assets/17423771966480.3957125846585592.png\">\u003C/p>\u003C/li>\u003C/ul>\u003Ch3 style='margin-top: 30px;margin-bottom: 15px;color: rgba(0, 0, 0, 0.85);cursor: pointer;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);'>\u003Cspan style=\"cursor: pointer;font-size: 20px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;font-weight: bold;display: block;\">消融研究\u003C/span>\u003C/h3>\u003Ch4 style='margin-top: 30px;margin-bottom: 15px;color: rgba(0, 0, 0, 0.85);cursor: pointer;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);'>\u003Cspan style=\"cursor: pointer;font-size: 18px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;font-weight: bold;display: block;\">专家的影响\u003C/span>\u003C/h4>\u003Cp style='margin-bottom: 0px;cursor: pointer;color: rgb(0, 0, 0);font-size: 16px;line-height: 1.8em;letter-spacing: normal;text-align: left;padding-top: 8px;padding-bottom: 8px;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;background-color: rgb(255, 255, 255);'>为了评估TradExpert框架中每个专家的有效性，我们创建了多个版本的TradExpert，每次移除一个特定的专家。通过比较这些修改版框架的性能，可以评估每个专家对TradExpert整体功能的影响。\u003C/p>\u003Cp style=\"text-align: center;\">\u003Cimg class=\"rich_pages wxw-img js_insertlocalimg\" data-croporisrc=\"https://mmbiz.qpic.cn/sz_mmbiz_png/YdtkbCEBMDGUdAY8lZNzGtpOobtrRND7d0oKhvv0p2108codE4sHibkLs5JW3QKB35TxiagkbsD30YD62DLWriabw/0?wx_fmt=png&from=appmsg\" data-cropx1=\"0\" data-cropx2=\"832\" data-cropy1=\"16.64\" data-cropy2=\"347.0628571428572\" data-imgfileid=\"100009304\" data-ratio=\"0.39663461538461536\" data-s=\"300,640\" data-type=\"jpeg\" data-w=\"832\" style=\"width: 394px;height: 156px;\" src=\"./assets/17423771973390.9786927578153641.jpeg\">\u003C/p>\u003Cul style='margin-top: 8px;margin-bottom: 8px;cursor: pointer;padding-left: 25px;color: rgb(0, 0, 0);font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);' class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">市场分析专家（Market Analyst）\u003C/strong>和\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">新闻分析专家（News Analyst）\u003C/strong>是最重要的，其缺失对年化收益率（AR）和波动率（AV）的影响最大。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">阿尔法因子专家（Alpha Expert）\u003C/strong>的影响小于市场分析专家和新闻分析专家。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">基本面分析专家（Fundamental Analyst）\u003C/strong>对日常交易指标影响最小，但为长期稳定性提供了重要支持，其缺失导致年化收益率和最大回撤（MD）的轻微变化。这表明TradExpert框架中各个专家的功能相互补充，共同实现最终决策和预测。\u003C/section>\u003C/li>\u003C/ul>\u003Ch4 style='margin-top: 30px;margin-bottom: 15px;color: rgba(0, 0, 0, 0.85);cursor: pointer;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);'>\u003Cspan style=\"cursor: pointer;font-size: 18px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;font-weight: bold;display: block;\">结构化数据推理的有效性\u003C/span>\u003C/h4>\u003Cp style='margin-bottom: 0px;cursor: pointer;color: rgb(0, 0, 0);font-size: 16px;line-height: 1.8em;letter-spacing: normal;text-align: left;padding-top: 8px;padding-bottom: 8px;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;background-color: rgb(255, 255, 255);'>通过将TradExpert-MA与传统模型（如用于结构化数据的OHLCV和阿尔法因子）进行比较，评估其推理能力：\u003C/p>\u003Cul style='margin-top: 8px;margin-bottom: 8px;cursor: pointer;padding-left: 25px;color: rgb(0, 0, 0);font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);' class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">基线模型采用基于遗传编程的符号回归模型，预测次日收益（(T+1)）的RankIC。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">TradExpert-MA仅使用阿尔法因子（移除新闻和基本面分析专家）进行比较，使用RankIC和RankICIR作为指标。\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">TradExpert-MA显著优于单独使用阿尔法因子的基线模型，显示了其对结构化数据的推理能力。\u003C/section>\u003Cp style=\"text-align: center;\">\u003Cimg class=\"rich_pages wxw-img js_insertlocalimg\" data-imgfileid=\"100009306\" data-ratio=\"0.2650273224043716\" data-s=\"300,640\" data-type=\"png\" data-w=\"732\" style=\"width: 356px;height: 94px;\" src=\"./assets/17423771967460.553658527632447.png\">\u003C/p>\u003C/li>\u003C/ul>\u003Ch4 style='margin-top: 30px;margin-bottom: 15px;color: rgba(0, 0, 0, 0.85);cursor: pointer;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);'>\u003Cspan style=\"cursor: pointer;font-size: 18px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;font-weight: bold;display: block;\">排序算法的选择\u003C/span>\u003C/h4>\u003Cp style='margin-bottom: 0px;cursor: pointer;color: rgb(0, 0, 0);font-size: 16px;line-height: 1.8em;letter-spacing: normal;text-align: left;padding-top: 8px;padding-bottom: 8px;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;background-color: rgb(255, 255, 255);'>TradExpert中实现Top-K排名的排序算法基于松弛比较，其核心为LLM比较器。为验证这种方法，我们与其他高效排序算法（如QuickSort和BubbleSort）进行了对比：\u003C/p>\u003Cul style='margin-top: 8px;margin-bottom: 8px;cursor: pointer;padding-left: 25px;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);' class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;line-height: 1.8em;letter-spacing: 0em;\">\u003Cspan style=\"color:#000000;\">\u003Cstrong>如下图\u003C/strong>\u003C/span>\u003Cspan style=\"color: rgb(1, 1, 1);\">显示，尽管松弛排序的时间复杂度较高，但在非传递性LLM比较器的场景下，通过增加比较次数显著提高了排名的准确性。\u003C/span>\u003C/section>\u003Cp style=\"text-align: center;\">\u003Cimg class=\"rich_pages wxw-img js_insertlocalimg\" data-imgfileid=\"100009308\" data-ratio=\"0.2828054298642534\" data-s=\"300,640\" data-type=\"png\" data-w=\"884\" style=\"width: 382px;height: 108px;\" src=\"./assets/17423771970390.5737928957743408.png\">\u003Cspan style='font-family: mp-quote, \"PingFang SC\", system-ui, -apple-system, BlinkMacSystemFont, \"Helvetica Neue\", \"Hiragino Sans GB\", \"Microsoft YaHei UI\", \"Microsoft YaHei\", Arial, sans-serif;font-size: var(--articleFontsize);letter-spacing: 0.034em;'>\u003C/span>\u003C/p>\u003C/li>\u003C/ul>\u003Cp style=\"display: none;\">\u003Cmp-style-type data-value=\"3\">\u003C/mp-style-type>\u003C/p>\u003C/div>",[257,266,274,277,285,293,301,309],{"id":258,"title_md5":259,"publish_date":260,"author_md5":261,"is_original":23,"collection":262,"summary_md5":263,"cover_url":264,"cover_url_1_1":265},176,"3e63182c3d10c34829a0722e235ae31b","2024-09-12","bc27fa490c4d0d525bac812fc0793534","#Google #All-In Summit 2024","9c460e968dd95fc3430f91859034ad25","article_res/cover/4302e820f0896a3a14b180d1309310b7.jpeg","article_res/cover/dcba5efbca0e9dbf4914b0ea74d2cf2c.jpeg",{"id":267,"title_md5":268,"publish_date":269,"author_md5":261,"is_original":23,"collection":270,"summary_md5":271,"cover_url":272,"cover_url_1_1":273},115,"9be7c20ff699d9e37e62d3ea2b0bd71b","2024-11-29","#Alibaba #AI Image Editor","bc3bdfca72b6c9e692f499d34f11022e","article_res/cover/60d1d7dd90e5e17de90d010dfc0f6207.jpeg","article_res/cover/a787a5ce21429b73ae4af162b1e3ecfd.jpeg",{"id":128,"title_md5":275,"publish_date":129,"author_md5":261,"is_original":23,"collection":130,"summary_md5":276,"cover_url":131,"cover_url_1_1":132},"291395f7b45ac2deb355492647b12b01","11dd1bde846454c9eef1c551ad46e943",{"id":278,"title_md5":279,"publish_date":280,"author_md5":261,"is_original":23,"collection":281,"summary_md5":282,"cover_url":283,"cover_url_1_1":284},163,"4b49dafcc1cfb589be46ba0bf494c739","2024-10-01","#Meta #LLM","cab783b89be708dcb7623245f0f5d31d","article_res/cover/cff77b1a39cc810ec45fe2d7ee6d3147.jpeg","article_res/cover/d02e205c34dd3ead44aa034048aadea9.jpeg",{"id":286,"title_md5":287,"publish_date":288,"author_md5":261,"is_original":23,"collection":289,"summary_md5":290,"cover_url":291,"cover_url_1_1":292},306,"5f19ad660109a98c9ca5535026ca01a0","2024-03-29","#AI Image Generator #Microsoft #LoRA","ec689c8e35f54bac86a6ff600c7962c7","article_res/cover/9e1700f6770672bbbcb97068b210e60e.jpeg","article_res/cover/472440aa68b9e44596e20e30df662484.jpeg",{"id":294,"title_md5":295,"publish_date":296,"author_md5":297,"is_original":4,"collection":5,"summary_md5":298,"cover_url":299,"cover_url_1_1":300},600,"46cef7f8fc57c5c597e5d6cb25566bba","2022-03-17","f44d4b523ff110f3126ff57530ea5253","38370a555596364c653822a90d7afe73","article_res/cover/2939be845a435111188513b939055861.jpeg","article_res/cover/95e241551f8799af8154cf25ea8c616e.jpeg",{"id":302,"title_md5":303,"publish_date":304,"author_md5":261,"is_original":23,"collection":305,"summary_md5":306,"cover_url":307,"cover_url_1_1":308},341,"b55735ef963870d9a24257601ab5d7be","2024-01-20","#AI Avatar #Tencent","1ce1dc3993f5e729e0cc63d4bbbbe60b","article_res/cover/a3050658715f87fbc909668bbb82cd85.jpeg","article_res/cover/f2b3ca4f1b3da75fc3e72e589183f822.jpeg",{"id":310,"title_md5":311,"publish_date":312,"author_md5":261,"is_original":23,"collection":313,"summary_md5":314,"cover_url":315,"cover_url_1_1":316},147,"a5d9baeffc6c34e1c950910658d7e753","2024-10-22","#State of AI Report 2024 #AI Game #AI Agent","7cf05490b7ddcb02531e8528786b4017","article_res/cover/d58dfe25c3723bd44d30cb29d48b77d3.jpeg","article_res/cover/8b34159832caf1ca2b3cdcf25ba4d32f.jpeg",{"related":318,"small":358},[319,327,335,342,350],{"id":320,"publish_date":321,"is_original":4,"collection":5,"cover_url":322,"cover_url_1_1":323,"title":324,"summary":325,"author":326},504,"2022-08-12","article_res/cover/ae8f1f2b4b4a442e47103f0e0af81808.jpeg","article_res/cover/f690a9c91d0fd600cdd92f1df57a4b47.jpeg","On how to explain something clearly that you don’t understand yourself","\"It's the best possible time to be alive when almost everything you thought you knew is wrong.\" \n- Tom Stoppard, Arcadia","Web3",{"id":328,"publish_date":329,"is_original":23,"collection":330,"cover_url":331,"cover_url_1_1":332,"title":333,"summary":334,"author":28},291,"2024-04-27","#AI 3D Generator","article_res/cover/da746312f3858a01f966e1c17ad1f9a3.jpeg","article_res/cover/53d099e12e83ee7f5c777e5320cbd173.jpeg","AI Generate 3D - AIUNI and Polycam trials","We believe that 3D capture is for everyone, so we made it easy. - Polycam",{"id":336,"publish_date":337,"is_original":4,"collection":5,"cover_url":338,"cover_url_1_1":339,"title":340,"summary":341,"author":28},335,"2024-01-26","article_res/cover/14bc34c5f592192af0f372971ce546cc.jpeg","article_res/cover/8b395057d151374561521132c9b01438.jpeg","Wallets in \"CRYPTO THESES 2024\"","If you own the world’s primary crypto user interfaces, you’re going to capture a good deal of value.",{"id":343,"publish_date":344,"is_original":23,"collection":345,"cover_url":346,"cover_url_1_1":347,"title":348,"summary":349,"author":28},169,"2024-09-25","#Object Detection","article_res/cover/b07f301cbebfee16c33372c32d24c139.jpeg","article_res/cover/d0f0dde93fcdf3d123d598db488e503f.jpeg","Supervision - Object detection in images and videos","We write your reusable computer vision tools. 💜",{"id":351,"publish_date":352,"is_original":23,"collection":353,"cover_url":354,"cover_url_1_1":355,"title":356,"summary":357,"author":28},220,"2024-07-12","#LLM #AI Agent","article_res/cover/773fcf4d426356b9a45db587f81070a9.jpeg","article_res/cover/5a1cd0f95085214308e40252c2c081a4.jpeg","Dify - LLM Application Development Platform","Dify is an open-source LLM app development platform.",[359,365,371],{"title":10,"list":360},[361,362,363,364],{"id":96,"publish_date":97,"is_original":23,"collection":98,"cover_url":99,"cover_url_1_1":100,"title":101,"summary":102,"author":28},{"id":104,"publish_date":105,"is_original":23,"collection":106,"cover_url":107,"cover_url_1_1":108,"title":109,"summary":110,"author":28},{"id":112,"publish_date":113,"is_original":23,"collection":114,"cover_url":115,"cover_url_1_1":116,"title":117,"summary":118,"author":28},{"id":166,"publish_date":167,"is_original":23,"collection":168,"cover_url":169,"cover_url_1_1":170,"title":171,"summary":172,"author":28},{"title":222,"list":366},[367,368,369,370],{"id":120,"publish_date":113,"is_original":23,"collection":121,"cover_url":122,"cover_url_1_1":123,"title":124,"summary":125,"author":28},{"id":166,"publish_date":167,"is_original":23,"collection":168,"cover_url":169,"cover_url_1_1":170,"title":171,"summary":172,"author":28},{"id":227,"publish_date":228,"is_original":23,"collection":229,"cover_url":230,"cover_url_1_1":231,"title":232,"summary":233,"author":28},{"id":235,"publish_date":236,"is_original":23,"collection":73,"cover_url":237,"cover_url_1_1":238,"title":239,"summary":240,"author":28},{"title":242,"list":372},[],[8,9,10],[8,12,13,14,9,10,15,16,17,18],["Reactive",245],1754646417178]