Existing Tool-Integrated Reasoning (TIR) models have effectively extended the question-answering capabilities of LLMs by incorporating external tools. However, real-world scenarios present numerous open-ended problems where fixed tools often fail to meet task requirements. Furthermore, the lack of self-optimization mechanisms means that erroneous tool outputs can mislead the LLM's responses. Additionally, the construction of existing tools entails significant manual effort, which consequently constrains their applicability. Recognizing that the reasoning traces of LLMs encapsulate implicit problem-solving capabilities, we propose UCT, a novel training-free framework that transforms agents from tool users to tool creators. This approach harvests reasoning experiences and distills them into reusable assets. This method transforms the agent from a mere tool user into a tool creator, enabling adaptive tool creation and self-updating during the inference process. We also introduce a memory consolidation mechanism to maintain the tool library, ensuring high reusability of retained experiential memory for subsequent reasoning tasks. This novel automated tool construction paradigm continuously improves tool quality during reasoning, allowing the overall agent system to progress without additional training. Extensive experiments demonstrate that our method serves as a novel paradigm for enhancing the capabilities of TIR models. In particular, the significant performance gains achieved +20.86%$\uparrow$ and +23.04%$\uparrow$ on benchmarks across multi-domain mathematical and scientific reasoning tasks validate the self-evolving capability of the agent.
DIRO & Institut Courtois, Université de Montréal（DIRO与Courtois研究所，蒙特利尔大学）；Mila – Québec AI Institute（魁北克人工智能研究所）；Microsoft Research（微软研究院）；Canada CIFAR AI Chair（加拿大CIFAR人工智能主席）
Experience Makes Skillful: Enabling Generalizable Medical Agent Reasoning via Self-Evolving Skill Memory
Fudan University（复旦大学）；Shanghai Artificial Intelligence Laboratory（上海人工智能实验室）；Shanghai Innovation Institute（上海创新研究院）；Huazhong University of Science and Technology（华中科技大学）
Reflect After Failure: Brain-Inspired Self-Evolving Agents for Embodied Spatial Intelligence
City University of Hong Kong（香港城市大学）；East China Normal University（华东师范大学）；University of Electronic Science and Technology of China（电子科技大学）；The Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳））；The University of Hong Kong（香港大学）
Co-Evolving LLM Decision and Skill Bank Agents for Long-Horizon Tasks
University of Maryland（马里兰大学）；University of Southern California（南加州大学）；Good Start Labs（Good Start实验室）；Independent Researcher（独立研究者）；Mohamed bin Zayed University of Artificial Intelligence（穆罕默德·本·扎耶德人工智能大学）
MemScope: Evolving Agent Memory Architectures through Localized Code Repair
State Key Laboratory of AI Safety（人工智能安全国家重点实验室）；Institute of Computing Technology, Chinese Academy of Sciences（中国科学院计算技术研究所）；University of Chinese Academy of Sciences（中国科学院大学）；Meituan（美团）
Your Agent May Misevolve: Emergent Risks in Self-evolving LLM Agents
Shanghai Artificial Intelligence Laboratory（上海人工智能实验室）；Shanghai Jiao Tong University（上海交通大学）；Renmin University of China（中国人民大学）；Princeton University（普林斯顿大学）；Hong Kong University of Science and Technology（香港科技大学）；Fudan University（复旦大学）
Travel Back To Move Forward: Retrospective Exploration and Evolving for Long Horizon Agents
University of Science and Technology of China（中国科学技术大学）；Shanghai Innovation Institute（上海创新研究院）；Facebook（脸书）；Zhejiang University（浙江大学）；Tsinghua University（清华大学）；Meituan（美团）；Fudan University（复旦大学）
Zhejiang University（浙江大学）；Huazhong University of Science and Technology（华中科技大学）；Xi’an Jiaotong University（西安交通大学）；National University of Defense Technology（国防科技大学）；Shanghai Jiao Tong University（上海交通大学）；Georgia Institute of Technology（佐治亚理工学院）；University of Science and Technology of China（中国科学技术大学）；Nanyang Technological University（南洋理工大学）；OPPO Research Institute（OPPO研究院）；Tianjin University（天津大学）；Chongqing University（重庆大学）；Alibaba Group（阿里巴巴集团）；Rakuten Group（乐天集团）
El Agente Forjador: Task-Driven Agent Generation for Quantum Simulation
Department of Computer Science, University of Toronto（多伦多大学计算机科学系）；Department of Chemistry, University of Toronto（多伦多大学化学系）；Department of Materials Science & Engineering, University of Toronto（多伦多大学材料科学与工程系）；Department of Chemical Engineering & Applied Chemistry, University of Toronto（多伦多大学化学工程与应用化学系）；Acceleration Consortium（加速联盟）；Vector Institute for Artificial Intelligence（人工智能矢量研究所）；Canadian Institute for Advanced Research (CIFAR)（加拿大高级研究 institute (CIFAR)）；NVIDIA
SEDM: Selective Self-Evolving Distributed Memory for Agents
Gradient Zhejiang University（Gradient浙江大学）；Gradient South China University of Technology（Gradient南方科技大学）；Gradient Waseda University（Gradient武藏大学）；Gradient University of Toronto（Gradient多伦多大学）；Gradient Rice University（Gradient里士满大学）；Gradient Emory University（Gradient埃默里大学）；Gradient University of Technology Sydney（Gradient悉尼技术大学）
MemQ: Integrating Q-Learning into Self-Evolving Memory Agents over Provenance DAGs
Shanghai Jiao Tong University（上海交通大学）；Shanghai Innovation Institute（上海创新研究院）；National University of Singapore（新加坡国立大学）；Xidian University（西安电子科技大学）；University of Science and Technology of China（中国科学技术大学）；MemTensor (Shanghai) Technology Co., Ltd.（MemTensor（上海）科技有限公司）
A/B Agent: A Self-Evolving Agent for Strategy Iteration in Industrial A/B Testing
The Hong Kong Polytechnic University（香港理工大学）；Kuaishou Technology（快手科技）；University of Electronic Science and Technology of China（电子科技大学）；Southwest Jiaotong University（西南交通大学）
