Large reasoning models (LRMs) like OpenAI-o1 have demonstrated impressive long stepwise reasoning capabilities through large-scale reinforcement learning. However, their extended reasoning processes often suffer from knowledge insufficiency, leading to frequent uncertainties and potential errors. To address this limitation, we introduce \textbf{Search-o1}, a framework that enhances LRMs with an agentic retrieval-augmented generation (RAG) mechanism and a Reason-in-Documents module for refining retrieved documents. Search-o1 integrates an agentic search workflow into the reasoning process, enabling dynamic retrieval of external knowledge when LRMs encounter uncertain knowledge points. Additionally, due to the verbose nature of retrieved documents, we design a separate Reason-in-Documents module to deeply analyze the retrieved information before injecting it into the reasoning chain, minimizing noise and preserving coherent reasoning flow. Extensive experiments on complex reasoning tasks in science, mathematics, and coding, as well as six open-domain QA benchmarks, demonstrate the strong performance of Search-o1. This approach enhances the trustworthiness and applicability of LRMs in complex reasoning tasks, paving the way for more reliable and versatile intelligent systems. The code is available at \url{https://github.com/sunnynexus/Search-o1}.
Reasoning RAG via System 1 or System 2: A Survey on Reasoning Agentic Retrieval-Augmented Generation for Industry Challenges
Beijing University of Posts and Telecommunications（北京邮电大学）；University of Georgia（佐治亚大学）；South China University of Technology（华南理工大学）；Technical University of Munich, University of Cologne（慕尼黑技术大学、科隆大学）；SenseTime Research（商汤科技研究院）；Qingyuan Research Institute, Shanghai Jiaotong University（青原研究院，上海交通大学）
DeepRead: Document Structure-Aware Reasoning to Enhance Agentic Search
State Key Laboratory of AI Safety, Institute of Computing Technology, Chinese Academy of Sciences (CAS)（人工智能安全国家重点实验室，计算技术研究所，中国科学院）；University of Chinese Academy of Sciences, CAS（中国科学院大学）；Wenlan School of Business, Zhongnan University of Economics（中南财经政法大学文澜商学院）
KnowCoder-A1: Incentivizing Agentic Reasoning Capability with Outcome Supervision for KBQA
Institute of Computing Technology, Chinese Academy of Sciences（中国科学院计算技术研究所）；State Key Laboratory of AI Safety（人工智能安全国家重点实验室）；School of Computer Science, University of Chinese Academy of Sciences（中国科学院大学计算机科学学院）
AgenticRag-R1: Agentic Reinforcement Learning with Stack Memory for Multi-Step Reasoning, Retrieval and Memorizing
National Engineering Research Center of Software Engineering, Peking University（北京大学国家软件工程研究中心）；School of Computer Science, Peking University（北京大学计算机学院）
Agentic AI with Orchestrator-Agent Trust: A Modular Visual Classification Framework with Trust-Aware Orchestration and RAG-Based Reasoning
University of the Peloponnese, Department of Informatics and Telecommunications（希腊皮埃蒙特大学信息与电信系）；Cornell University, Department of Biological and Environmental Engineering（康奈尔大学生物与环境工程系）
Scaling Agentic Reinforcement Learning for Tool-Integrated Reasoning in VLMs
Virginia Tech（弗吉尼亚理工大学）；Emory University（埃默里大学）；KAUST（阿联酋卡塔尔大学）；Georgia Tech（佐治亚理工学院）；Cisco（思科系统）；TAMU（德克萨斯大学奥斯汀分校）；UT Southwestern Medical Center（德克萨斯西南医学中心）；Eigen AI
A Survey of Frontiers in LLM Reasoning: Inference Scaling, Learning to Reason, and Agentic Systems
Salesforce AI Research（Salesforce AI研究）；National University of Singapore（国立新加坡大学）；Nanyang Technological University（南洋理工大学）；The Hong Kong University of Science and Technology (Guangzhou)（香港科学与技术大学（广州））；A*STAR, Singapore（新加坡A*STAR）
TMLR Group Department of Computer Science Hong Kong Baptist University（香港 Baptist 大学计算机科学系 TMLR 组）；RIKEN AIP；Cooperative Medianet Innovation Center Shanghai Jiao Tong University（上海交通大学合作中立创新中心）；Stanford University（斯坦福大学）；Sydney AI Centre The University of Sydney（悉尼大学悉尼AI中心）；The University of Tokyo（东京大学）
Octopus: Agentic Multimodal Reasoning with Six-Capability Orchestration
Sun Yat-sen University（中山大学）；Shanghai Jiao Tong University（上海交通大学）；Zhejiang University（浙江大学）；Tsinghua University（清华大学）；Peking University（北京大学）；The Hong Kong University of Science and Technology（香港科技大学）；University of Chinese Academy of Sciences（中国科学院大学）
TimeSage-MT: A Multi-Turn Benchmark for Evaluating Agentic Time Series Reasoning
University of Oxford（牛津大学）；VulpiVox Intelligence；Eindhoven University of Technology（埃因霍温理工大学）；Griffith University（格里菲斯大学）；Squirrel Ai Learning；East China Normal University（华东师范大学）
AgenticRAGTracer: A Hop-Aware Benchmark for Diagnosing Multi-Step Retrieval Reasoning in Agentic RAG
University of Science and Technology Beijing（北京科技大学）；Peking University（北京大学）；Zhongguancun Academy（中关村学院）；Beijing Key Laboratory of Data Intelligence and Security (Peking University)（北京市数据智能与安全重点实验室（北京大学））
