[{"data":1,"prerenderedAt":205},["ShallowReactive",2],{"DlFXI4Eibt_Bn9lrEZz1TYbHCWFZj3IvqwHQSEW-Exc":3,"AnsFtxpoPX6zerNZct0oO8tKtHgHbjaNyhZ9XSw0uj4":194},{"code":4,"msg":5,"data":6},0,"",{"category":7,"tag":11,"hot":39,"new":78,"banner":118,"data":143,"cache":193},[8,9,10],"Agent","OpenAI","LLM",[12,14,17,20,23,25,27,30,33,36],{"title":8,"total":13},39,{"title":15,"total":16},"Google",44,{"title":18,"total":19},"Nvidia",13,{"title":21,"total":22},"Claude",11,{"title":9,"total":24},35,{"title":10,"total":26},85,{"title":28,"total":29},"DeepSeek",9,{"title":31,"total":32},"OCR",1,{"title":34,"total":35},"Chat",7,{"title":37,"total":38},"Generator",116,[40,48,55,64,71],{"id":41,"publish_date":42,"is_original":4,"collection":5,"cover_url":43,"cover_url_1_1":44,"title":45,"summary":46,"author":47},557,"2022-04-29","article_res/cover/7a9b1375ed9bb298154981bae42b794d.jpeg","article_res/cover/afa281dd52bc0454e6735daa8e6b0706.jpeg","Translation and summary of Messari Report [2.8 Kristin Smith, Blockchain Association and Katie Haun, a16z]","We need unity and speed right now.","Translation",{"id":49,"publish_date":50,"is_original":4,"collection":5,"cover_url":51,"cover_url_1_1":52,"title":53,"summary":54,"author":47},531,"2022-05-25","article_res/cover/e8362057f8fa189594c60afdfaaeb6e5.jpeg","article_res/cover/8ea08d0d6fa7eee6b57ed4ec61b61ad6.jpeg","Decentralized Society: Finding Web3’s Soul / Decentralized Society: Finding the Soul of Web3 -7","Decentralization through Pluralism When analyzing ecosystems, it's desirable to measure how decentralized it is.",{"id":56,"publish_date":57,"is_original":32,"collection":58,"cover_url":59,"cover_url_1_1":60,"title":61,"summary":62,"author":63},127,"2024-11-14","#Google #AI Game #World Model #AI Story","article_res/cover/0233a875b7ec2debf59779e311547569.jpeg","article_res/cover/6ffddb6ae4914b3c699493311aa9f198.jpeg","Google Launches \"Unbounded\": A Generative Infinite Character Life Simulation Game","Unbounded: A Generative Infinite Game of Character Life Simulation","Renee's Entrepreneurial Journey",{"id":13,"publish_date":65,"is_original":32,"collection":66,"cover_url":67,"cover_url_1_1":68,"title":69,"summary":70,"author":63},"2025-02-14","#Deep Dive into LLMs #Andrej Karpathy #LLM #Tool Use #Hallucination","article_res/cover/11e858ad6b74dfa80f923d549b62855c.jpeg","article_res/cover/615e1b320f1fc163edc1d2d154a6de33.jpeg","Andrej Karpathy's in-depth explanation of LLM (Part 4): Hallucinations","hallucinations, tool use, knowledge/working memory",{"id":72,"publish_date":73,"is_original":4,"collection":5,"cover_url":74,"cover_url_1_1":75,"title":76,"summary":77,"author":47},579,"2022-04-07","article_res/cover/39387376ba28447af1eb40576b9df215.jpeg","article_res/cover/02727ede8551ed49901d0abe6d6305b7.jpeg","Messari Report Translation and Summary 【1-7 Surviving the Winter】","I’d be more cautious here: 10 year and 10 hour thinking only.",[79,87,95,103,111],{"id":80,"publish_date":81,"is_original":32,"collection":82,"cover_url":83,"cover_url_1_1":84,"title":85,"summary":86,"author":63},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":88,"publish_date":89,"is_original":32,"collection":90,"cover_url":91,"cover_url_1_1":92,"title":93,"summary":94,"author":63},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":96,"publish_date":97,"is_original":32,"collection":98,"cover_url":99,"cover_url_1_1":100,"title":101,"summary":102,"author":63},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":104,"publish_date":105,"is_original":32,"collection":106,"cover_url":107,"cover_url_1_1":108,"title":109,"summary":110,"author":63},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":112,"publish_date":105,"is_original":32,"collection":113,"cover_url":114,"cover_url_1_1":115,"title":116,"summary":117,"author":63},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",[119,127,135],{"id":120,"publish_date":121,"is_original":32,"collection":122,"cover_url":123,"cover_url_1_1":124,"title":125,"summary":126,"author":63},160,"2024-10-04","#Philosophy","article_res/cover/496990c49211e8b7f996b7d39c18168e.jpeg","article_res/cover/14dbaa1ade9cb4316d5829423a900362.jpeg","Time","The fungus of the morning does not know the waxing and waning of the moon, and the cicada does not know the seasons; this is a short life. To the south of the state of Chu there is a dark spirit which regards five hundred years as spring and five hundred years as autumn. In ancient times there was a great tree called the Ming which regarded eight thousand years as spring and eight thousand years as autumn; this is a long life.",{"id":128,"publish_date":129,"is_original":32,"collection":130,"cover_url":131,"cover_url_1_1":132,"title":133,"summary":134,"author":63},98,"2024-12-17","#AI Video Generator #Sora #Pika","article_res/cover/3b86e85d03fff4f356a3e4cf2bb329c9.jpeg","article_res/cover/5fa5c20ad0b40f8f544d257c0ef02938.jpeg","Pika 2.0 video generation officially released: effect comparison with Sora","今天，我们推出了Pika 2.0模型。卓越的文字对齐效果。惊人的视觉表现。还有✨场景成分✨",{"id":136,"publish_date":137,"is_original":32,"collection":138,"cover_url":139,"cover_url_1_1":140,"title":141,"summary":142,"author":63},71,"2025-01-14","#Nvidia #World Foundation Model #Cosmos #Physical AI #Embodied AI","article_res/cover/feddf8c832dfb45d28804291f6a42a9e.jpeg","article_res/cover/d6bc2f1186d96b78228c2283a17a3645.jpeg","NVIDIA's Cosmos World Model","Cosmos World Foundation Model Platform for Physical AI",[144,163,188],{"title":8,"items":145},[146,147,155],{"id":104,"publish_date":105,"is_original":32,"collection":106,"cover_url":107,"cover_url_1_1":108,"title":109,"summary":110,"author":63},{"id":148,"publish_date":149,"is_original":32,"collection":150,"cover_url":151,"cover_url_1_1":152,"title":153,"summary":154,"author":63},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":156,"publish_date":157,"is_original":32,"collection":158,"cover_url":159,"cover_url_1_1":160,"title":161,"summary":162,"author":63},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",{"title":9,"items":164},[165,172,180],{"id":166,"publish_date":157,"is_original":32,"collection":167,"cover_url":168,"cover_url_1_1":169,"title":170,"summary":171,"author":63},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":173,"publish_date":174,"is_original":4,"collection":175,"cover_url":176,"cover_url_1_1":177,"title":178,"summary":179,"author":63},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":181,"publish_date":182,"is_original":4,"collection":183,"cover_url":184,"cover_url_1_1":185,"title":186,"summary":187,"author":63},417,"2023-08-24","#OpenAI","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.",{"title":10,"items":189},[190,191,192],{"id":88,"publish_date":89,"is_original":32,"collection":90,"cover_url":91,"cover_url_1_1":92,"title":93,"summary":94,"author":63},{"id":96,"publish_date":97,"is_original":32,"collection":98,"cover_url":99,"cover_url_1_1":100,"title":101,"summary":102,"author":63},{"id":104,"publish_date":105,"is_original":32,"collection":106,"cover_url":107,"cover_url_1_1":108,"title":109,"summary":110,"author":63},true,{"code":4,"msg":5,"data":195},{"id":196,"publish_date":197,"is_original":32,"collection":198,"articles_id":199,"cover_url":200,"cover_url_1_1":201,"title":202,"summary":203,"author":63,"content":204},12,"2025-03-09","#Oxford #Reasoning #LLM #Tool Use","MaVws1StGyYDGZRBbpw9xA","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","\u003Cdiv class=\"rich_media_content js_underline_content\n                       autoTypeSetting24psection\n            \" id=\"js_content\">\u003Cp style='box-sizing: border-box;margin: 0px;;color: rgb(0, 0, 0);font-size: 16px;line-height: 1.8em;letter-spacing: normal;text-align: left;text-indent: 0px;padding: 8px 0px;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-style: normal;font-variant-ligatures: normal;font-variant-caps: normal;font-weight: 400;orphans: 2;text-transform: none;widows: 2;word-spacing: 0px;-webkit-text-stroke-width: 0px;white-space: normal;background-color: rgb(255, 255, 255);text-decoration-thickness: initial;text-decoration-style: initial;text-decoration-color: initial;'>\u003Cspan leaf=\"\">Three Chinese students from Oxford University proposed a new framework called\u003C/span>\u003Cstrong style=\"box-sizing: border-box;font-weight: bold;;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;margin: 0px;padding: 0px;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">\u003Cspan leaf=\"\">Agentic Reasoning\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">Toolbench, which aims to significantly enhance the reasoning capabilities of large language models (LLMs) by integrating external tools through tool-using agents.\u003C/span>\u003C/p>\u003Cp style='box-sizing: border-box;margin: 0px;;color: rgb(0, 0, 0);font-size: 16px;line-height: 1.8em;letter-spacing: normal;text-align: left;text-indent: 0px;padding: 8px 0px;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-style: normal;font-variant-ligatures: normal;font-variant-caps: normal;font-weight: 400;orphans: 2;text-transform: none;widows: 2;word-spacing: 0px;-webkit-text-stroke-width: 0px;white-space: normal;background-color: rgb(255, 255, 255);text-decoration-thickness: initial;text-decoration-style: initial;text-decoration-color: initial;'>\u003Cspan leaf=\"\">Unlike traditional LLMs that rely entirely on internal reasoning, Agentic Reasoning dynamically invokes external tools such as web search, code execution, and structured reasoning-context memory to solve complex problems requiring in-depth research and multi-step logical reasoning.\u003C/span>\u003C/p>\u003Cp style='box-sizing: border-box;margin: 0px;;color: rgb(0, 0, 0);font-size: 16px;line-height: 1.8em;letter-spacing: normal;text-align: left;text-indent: 0px;padding: 8px 0px;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-style: normal;font-variant-ligatures: normal;font-variant-caps: normal;font-weight: 400;orphans: 2;text-transform: none;widows: 2;word-spacing: 0px;-webkit-text-stroke-width: 0px;white-space: normal;background-color: rgb(255, 255, 255);text-decoration-thickness: initial;text-decoration-style: initial;text-decoration-color: initial;'>\u003Cspan leaf=\"\">The framework introduces an agent named\u003C/span>\u003Cstrong style=\"box-sizing: border-box;font-weight: bold;;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;margin: 0px;padding: 0px;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">\u003Cspan leaf=\"\">Mind Map agent\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">Knowledge Weaver, which can construct structured knowledge graphs to clearly track logical relationships, effectively improving deductive reasoning abilities. Additionally, by integrating web search and programming agents, the model can obtain information and perform computational analysis in real time, thereby enhancing reasoning accuracy and decision-making quality.\u003C/span>\u003C/p>\u003Cp style='box-sizing: border-box;margin: 0px;;color: rgb(0, 0, 0);font-size: 16px;line-height: 1.8em;letter-spacing: normal;text-align: left;text-indent: 0px;padding: 8px 0px;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-style: normal;font-variant-ligatures: normal;font-variant-caps: normal;font-weight: 400;orphans: 2;text-transform: none;widows: 2;word-spacing: 0px;-webkit-text-stroke-width: 0px;white-space: normal;background-color: rgb(255, 255, 255);text-decoration-thickness: initial;text-decoration-style: initial;text-decoration-color: initial;'>\u003Cspan leaf=\"\">Below is a polished version of your provided content in Chinese, retaining the professional English terminology and original meaning while adjusting it for a more suitable expression style for Chinese readers and providing a clear structure:\u003C/span>\u003C/p>\u003Ch2 style='box-sizing: border-box;margin: 30px 0px 15px;color: rgba(0, 0, 0, 0.85);font-weight: 500;;padding: 0px;display: block;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-style: normal;font-variant-ligatures: normal;font-variant-caps: normal;letter-spacing: normal;orphans: 2;text-align: left;text-indent: 0px;text-transform: none;widows: 2;word-spacing: 0px;-webkit-text-stroke-width: 0px;white-space: normal;background-color: rgb(255, 255, 255);text-decoration-thickness: initial;text-decoration-style: initial;text-decoration-color: initial;'>\u003Cspan style=\"box-sizing: border-box;;font-size: 22px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;text-align: left;font-weight: bold;display: block;\">\u003Cspan leaf=\"\">Overall Process\u003C/span>\u003C/span>\u003C/h2>\u003Csection style=\"text-align: center;\" nodeleaf=\"\">\u003Cimg class=\"rich_pages wxw-img js_insertlocalimg\" data-ratio=\"0.56286836935167\" data-s=\"300,640\" data-type=\"png\" data-w=\"1018\" type=\"block\" data-imgfileid=\"100010727\" style=\"height: auto !important;\" src=\"https://res.cooltool.vip/article_res/assets/17423769528740.9874541051498564.png\">\u003C/section>\u003Csection style=\"text-align: center;\" nodeleaf=\"\">\u003Cimg class=\"rich_pages wxw-img js_insertlocalimg\" data-ratio=\"2.1776061776061777\" data-s=\"300,640\" data-type=\"png\" data-w=\"518\" type=\"block\" data-imgfileid=\"100010728\" style=\"height: auto !important;\" src=\"https://res.cooltool.vip/article_res/assets/17423769531870.7547011423107068.png\">\u003C/section>\u003Ch2 style='box-sizing: border-box;margin: 30px 0px 15px;color: rgba(0, 0, 0, 0.85);font-weight: 500;;padding: 0px;display: block;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-style: normal;font-variant-ligatures: normal;font-variant-caps: normal;letter-spacing: normal;orphans: 2;text-align: left;text-indent: 0px;text-transform: none;widows: 2;word-spacing: 0px;-webkit-text-stroke-width: 0px;white-space: normal;background-color: rgb(255, 255, 255);text-decoration-thickness: initial;text-decoration-style: initial;text-decoration-color: initial;'>\u003Cspan style=\"box-sizing: border-box;;font-size: 22px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;text-align: left;font-weight: bold;display: block;\">\u003Cspan leaf=\"\">Experimental Evaluation and Case Analysis\u003C/span>\u003C/span>\u003C/h2>\u003Cp style='box-sizing: border-box;margin: 0px;;color: rgb(0, 0, 0);font-size: 16px;line-height: 1.8em;letter-spacing: normal;text-align: left;text-indent: 0px;padding: 8px 0px;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-style: normal;font-variant-ligatures: normal;font-variant-caps: normal;font-weight: 400;orphans: 2;text-transform: none;widows: 2;word-spacing: 0px;-webkit-text-stroke-width: 0px;white-space: normal;background-color: rgb(255, 255, 255);text-decoration-thickness: initial;text-decoration-style: initial;text-decoration-color: initial;'>\u003Cspan leaf=\"\">The research team conducted the following experiments and case analyses, demonstrating the advantages of\u003C/span>\u003Cstrong style=\"box-sizing: border-box;font-weight: bold;;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;margin: 0px;padding: 0px;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">\u003Cspan leaf=\"\">Agentic Reasoning\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">Agentic Reasoning:\u003C/span>\u003C/p>\u003Ch4 style='box-sizing: border-box;margin: 30px 0px 15px;color: rgba(0, 0, 0, 0.85);font-weight: 500;;padding: 0px;display: block;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;font-style: normal;font-variant-ligatures: normal;font-variant-caps: normal;letter-spacing: normal;orphans: 2;text-align: left;text-indent: 0px;text-transform: none;widows: 2;word-spacing: 0px;-webkit-text-stroke-width: 0px;white-space: normal;background-color: rgb(255, 255, 255);text-decoration-thickness: initial;text-decoration-style: initial;text-decoration-color: initial;'>\u003Cspan style=\"box-sizing: border-box;;font-size: 18px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;text-align: left;font-weight: bold;display: block;\">\u003Cspan leaf=\"\">Case One: Doctoral-Level Scientific Reasoning Task (GPQA)\u003C/span>\u003C/span>\u003C/h4>\u003Cul style='box-sizing: border-box;margin: 8px 0px;;list-style-type: disc;padding: 0px 0px 0px 25px;color: rgb(0, 0, 0);font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;font-style: normal;font-variant-ligatures: normal;font-variant-caps: normal;font-weight: 400;letter-spacing: normal;orphans: 2;text-align: left;text-indent: 0px;text-transform: none;widows: 2;word-spacing: 0px;-webkit-text-stroke-width: 0px;white-space: normal;background-color: rgb(255, 255, 255);text-decoration-thickness: initial;text-decoration-style: initial;text-decoration-color: initial;' class=\"list-paddingleft-1\">\u003Cli style=\"box-sizing: border-box;;\">\u003Csection style=\"box-sizing: border-box;;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);font-size: 16px;line-height: 1.8em;letter-spacing: 0em;text-align: left;font-weight: normal;\">\u003Cspan leaf=\"\">Evaluation was performed on GPQA, a high-difficulty scientific reasoning task.\u003C/span>\u003C/section>\u003C/li>\u003Cli style=\"box-sizing: border-box;;\">\u003Csection style=\"box-sizing: border-box;;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);font-size: 16px;line-height: 1.8em;letter-spacing: 0em;text-align: left;font-weight: normal;\">\u003Cspan leaf=\"\">It significantly outperforms existing leading RAG (Retrieval-Augmented Generation) systems and closed-source LLMs.\u003C/span>\u003C/section>\u003Csection style=\"text-align: center;\" nodeleaf=\"\">\u003Cimg class=\"rich_pages wxw-img js_insertlocalimg\" data-ratio=\"1.0671641791044777\" data-s=\"300,640\" data-type=\"png\" data-w=\"536\" type=\"block\" data-imgfileid=\"100010729\" style=\"height: auto !important;\" src=\"https://res.cooltool.vip/article_res/assets/17423769528790.9727883867046918.png\">\u003C/section>\u003C/li>\u003C/ul>\u003Ch4 style='box-sizing: border-box;margin: 30px 0px 15px;color: rgba(0, 0, 0, 0.85);font-weight: 500;;padding: 0px;display: block;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;font-style: normal;font-variant-ligatures: normal;font-variant-caps: normal;letter-spacing: normal;orphans: 2;text-align: left;text-indent: 0px;text-transform: none;widows: 2;word-spacing: 0px;-webkit-text-stroke-width: 0px;white-space: normal;background-color: rgb(255, 255, 255);text-decoration-thickness: initial;text-decoration-style: initial;text-decoration-color: initial;'>\u003Cspan style=\"box-sizing: border-box;;font-size: 18px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;text-align: left;font-weight: bold;display: block;\">\u003Cspan leaf=\"\">Case Two: Domain-Specific Deep Research Tasks\u003C/span>\u003C/span>\u003C/h4>\u003Cul style='box-sizing: border-box;margin: 8px 0px;;list-style-type: disc;padding: 0px 0px 0px 25px;color: rgb(0, 0, 0);font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;font-style: normal;font-variant-ligatures: normal;font-variant-caps: normal;font-weight: 400;letter-spacing: normal;orphans: 2;text-align: left;text-indent: 0px;text-transform: none;widows: 2;word-spacing: 0px;-webkit-text-stroke-width: 0px;white-space: normal;background-color: rgb(255, 255, 255);text-decoration-thickness: initial;text-decoration-style: initial;text-decoration-color: initial;' class=\"list-paddingleft-1\">\u003Cli style=\"box-sizing: border-box;;\">\u003Csection style=\"box-sizing: border-box;;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);font-size: 16px;line-height: 1.8em;letter-spacing: 0em;text-align: left;font-weight: normal;\">\u003Cspan leaf=\"\">In domain-specific deep research questions, Agentic Reasoning significantly enhances expert-level knowledge synthesis and reasoning accuracy.\u003C/span>\u003C/section>\u003Csection style=\"text-align: center;\" nodeleaf=\"\">\u003Cimg class=\"rich_pages wxw-img js_insertlocalimg\" data-ratio=\"0.6904276985743381\" data-s=\"300,640\" data-type=\"png\" data-w=\"491\" type=\"block\" data-imgfileid=\"100010732\" style=\"height: auto !important;\" src=\"https://res.cooltool.vip/article_res/assets/17423769528850.10397888690793011.png\">\u003C/section>\u003C/li>\u003C/ul>\u003Ch4 style='box-sizing: border-box;margin: 30px 0px 15px;color: rgba(0, 0, 0, 0.85);font-weight: 500;;padding: 0px;display: block;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;font-style: normal;font-variant-ligatures: normal;font-variant-caps: normal;letter-spacing: normal;orphans: 2;text-align: left;text-indent: 0px;text-transform: none;widows: 2;word-spacing: 0px;-webkit-text-stroke-width: 0px;white-space: normal;background-color: rgb(255, 255, 255);text-decoration-thickness: initial;text-decoration-style: initial;text-decoration-color: initial;'>\u003Cspan style=\"box-sizing: border-box;;font-size: 18px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;text-align: left;font-weight: bold;display: block;\">\u003Cspan leaf=\"\">Case Three: Misleading Question Answering\u003C/span>\u003C/span>\u003C/h4>\u003Cul style='box-sizing: border-box;margin: 8px 0px;;list-style-type: disc;padding: 0px 0px 0px 25px;color: rgb(0, 0, 0);font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;font-style: normal;font-variant-ligatures: normal;font-variant-caps: normal;font-weight: 400;letter-spacing: normal;orphans: 2;text-align: left;text-indent: 0px;text-transform: none;widows: 2;word-spacing: 0px;-webkit-text-stroke-width: 0px;white-space: normal;background-color: rgb(255, 255, 255);text-decoration-thickness: initial;text-decoration-style: initial;text-decoration-color: initial;' class=\"list-paddingleft-1\">\u003Cli style=\"box-sizing: border-box;;\">\u003Csection style=\"box-sizing: border-box;;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);font-size: 16px;line-height: 1.8em;letter-spacing: 0em;text-align: left;font-weight: normal;\">\u003Cspan leaf=\"\">The paper presents a special misleading question that caused most existing LLM models to produce incorrect answers, but\u003C/span>\u003Cstrong style=\"box-sizing: border-box;font-weight: bold;;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;margin: 0px;padding: 0px;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">\u003Cspan leaf=\"\">Agentic Reasoning\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">Agentic Reasoning successfully answered correctly.\u003C/span>\u003C/section>\u003Csection style=\"text-align: center;\" nodeleaf=\"\">\u003Cimg class=\"rich_pages wxw-img js_insertlocalimg\" data-ratio=\"0.5648604269293924\" data-s=\"300,640\" data-type=\"png\" data-w=\"609\" type=\"block\" data-imgfileid=\"100010731\" style=\"height: auto !important;\" src=\"https://res.cooltool.vip/article_res/assets/17423769530990.7682544968976319.png\">\u003C/section>\u003C/li>\u003C/ul>\u003Ch3 style='box-sizing: border-box;margin: 30px 0px 15px;color: rgba(0, 0, 0, 0.85);font-weight: 500;;padding: 0px;display: block;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-style: normal;font-variant-ligatures: normal;font-variant-caps: normal;letter-spacing: normal;orphans: 2;text-align: left;text-indent: 0px;text-transform: none;widows: 2;word-spacing: 0px;-webkit-text-stroke-width: 0px;white-space: normal;background-color: rgb(255, 255, 255);text-decoration-thickness: initial;text-decoration-style: initial;text-decoration-color: initial;'>\u003Cspan style=\"box-sizing: border-box;;font-size: 20px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;text-align: left;font-weight: bold;display: block;\">\u003Cspan leaf=\"\">Application of Mind Map in the \"Werewolf\" Game\u003C/span>\u003C/span>\u003C/h3>\u003Csection style=\"text-align: center;\" nodeleaf=\"\">\u003Cimg class=\"rich_pages wxw-img js_insertlocalimg\" data-imgfileid=\"100010733\" data-ratio=\"1.1419098143236075\" data-s=\"300,640\" data-type=\"png\" data-w=\"754\" type=\"block\" style=\"height: auto !important;\" src=\"https://res.cooltool.vip/article_res/assets/17423769542880.7749740797971383.png\">\u003C/section>\u003Ch2 style='box-sizing: border-box;margin: 30px 0px 15px;color: rgba(0, 0, 0, 0.85);font-weight: 500;;padding: 0px;display: block;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-style: normal;font-variant-ligatures: normal;font-variant-caps: normal;letter-spacing: normal;orphans: 2;text-align: left;text-indent: 0px;text-transform: none;widows: 2;word-spacing: 0px;-webkit-text-stroke-width: 0px;white-space: normal;background-color: rgb(255, 255, 255);text-decoration-thickness: initial;text-decoration-style: initial;text-decoration-color: initial;'>\u003Cspan style=\"box-sizing: border-box;;font-size: 22px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;text-align: left;font-weight: bold;display: block;\">\u003Cspan leaf=\"\">Code\u003C/span>\u003C/span>\u003C/h2>\u003Cp style='box-sizing: border-box;margin: 0px;;color: rgb(0, 0, 0);font-size: 16px;line-height: 1.8em;letter-spacing: normal;text-align: left;text-indent: 0px;padding: 8px 0px;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-style: normal;font-variant-ligatures: normal;font-variant-caps: normal;font-weight: 400;orphans: 2;text-transform: none;widows: 2;word-spacing: 0px;-webkit-text-stroke-width: 0px;white-space: normal;background-color: rgb(255, 255, 255);text-decoration-thickness: initial;text-decoration-style: initial;text-decoration-color: initial;'>\u003Cspan leaf=\"\">The paper's code has been open-sourced: https://github.com/theworldofagents/Agentic-Reasoning\u003C/span>\u003C/p>\u003Cp style=\"display: none;\">\u003Cmp-style-type data-value=\"3\">\u003C/mp-style-type>\u003C/p>\u003C/div>",1752585426411]