Molecular editing and optimization are multi-step problems that require iteratively improving properties while keeping molecules chemically valid and structurally similar. We frame both tasks as sequential, tool-guided decisions and introduce MolAct, an agentic reinforcement learning framework that employs a two-stage training paradigm: first building editing capability, then optimizing properties while reusing the learned editing behaviors. To the best of our knowledge, this is the first work to formalize molecular design as an Agentic Reinforcement Learning problem, where an LLM agent learns to interleave reasoning, tool-use, and molecular optimization. The framework enables agents to interact in multiple turns, invoking chemical tools for validity checking, property assessment, and similarity control, and leverages their feedback to refine subsequent edits. We instantiate the MolAct framework to train two model families: MolEditAgent for molecular editing tasks and MolOptAgent for molecular optimization tasks. In molecular editing, MolEditAgent-7B delivers 100, 95, and 98 valid add, delete, and substitute edits, outperforming strong closed "thinking" baselines such as DeepSeek-R1; MolEditAgent-3B approaches the performance of much larger open "thinking" models like Qwen3-32B-think. In molecular optimization, MolOptAgent-7B (trained on MolEditAgent-7B) surpasses the best closed "thinking" baseline (e.g., Claude 3.7) on LogP and remains competitive on solubility, while maintaining balanced performance across other objectives. These results highlight that treating molecular design as a multi-step, tool-augmented process is key to reliable and interpretable improvements.
City Editing: Hierarchical Agentic Execution for Dependency-Aware Urban Geospatial Modification
University of Kansas, Lawrence, KS, USA（堪萨斯大学）；Seoul National University, Seoul, South Korea（首尔国立大学）；University of Florida, Gainesville, FL, USA（佛罗里达大学）；NEC Laboratories America, Princeton, NJ, USA（NEC美国实验室）；Clemson University, Clemson, SC, USA（克莱姆森大学）；Arizona State University, Tempe, AZ, USA（亚利桑那州立大学）
Prompt-Driven Agentic Video Editing System: Autonomous Comprehension of Long-Form, Story-Driven Media
University of British Columbia（不列颠哥伦比亚大学）；University of Bristol（布里斯托大学）；Department of Engineering, University of Cambridge（剑桥大学工程系）；School of Computer Science, University of Bristol（布里斯托大学计算机科学学院）
The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））；DeepWisdom；Singapore University of Technology and Design（新加坡科技设计大学）；Nanyang Technological University（南洋理工大学）；Shanghai Jiao Tong University（上海交通大学）；Tsinghua University（清华大学）；Université de Montréal & Mila（蒙特利尔大学及Mila）
Memory as Action: Autonomous Context Curation for Long-Horizon Agentic Tasks
School of Computer Science and Technology, Beijing Jiaotong University（北京交通大学计算机科学与技术学院）；Hithink Research（慧思科技）；The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））；Huawei Noah’s Ark Lab（华为诺亚实验室）；Peng Cheng Lab（鹏城实验室）
SSE-Bio: A Structured Self-Evolving Agent with Agentic Retrieval Policy for Multi-Hop Biomedical Reasoning
School of Computing Science, University of Glasgow（格拉斯哥大学计算科学学院）；Brigham and Women’s Hospital, Harvard Medical School, Harvard University（哈佛大学医学院附属布莱根妇女医院）；Language Technology Lab, University of Cambridge（剑桥大学语言技术实验室）；School of Natural and Computing Science, University of Aberdeen（阿伯丁大学自然与计算科学学院）；School of Cancer Sciences, University of Glasgow（格拉斯哥大学癌症科学学院）；Cancer Research UK Scotland Institute（英国癌症研究苏格兰研究所）
Towards Human-Like Interactive Speech Recognition With Agentic Correction and Semantic Evaluation
College of Artificial Intelligence, Xi’an Jiaotong University（西安交通大学人工智能学院）；X-LANCE Lab, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University（上海交通大学电子信息与电气工程学院X-LANCE实验室）；The Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳））；Fudan University（复旦大学）；Tongyi Fun Team, Alibaba Group（阿里云通义团队）
AutoDesign: Meta-Harness Optimization for Long-Horizon Agentic Design
Meituan（美团）；MBZUAI（Mohamed bin Zayed University of Artificial Intelligence）；Huazhong University of Science and Technology（华中科技大学）；Peking University（北京大学）；Tsinghua University（清华大学）；The Chinese University of Hong Kong（香港中文大学）；Shanghai Jiao Tong University（上海交通大学）
University of British Columbia（不列颠哥伦比亚大学）；Vector Institute（向量研究所）；Kolors Team, Kuaishou Technology（快手团队）；Carnegie Mellon University（卡内基梅隆大学）；University of Waterloo（滑铁卢大学）；Etude AI；Tsinghua University（清华大学）；Georgia Institute of Technology（佐治亚理工学院）
Beyond Coherence: Benchmarking Professional Editing-Technique Execution in Multi-Shot Audio-Video Generation
Shanghai Jiao Tong University（上海交通大学）；Alibaba Group（阿里巴巴集团）；Fudan University（复旦大学）；UT Austin（德克萨斯大学奥斯汀分校）；Institute of Software, Chinese Academy of Sciences（中国科学院软件研究所）
