As Large Language Models (LLMs) move from curated training sets into open-ended real-world environments, a fundamental limitation emerges: static training cannot keep pace with continual deployment environment change. Scaling training-time and inference-time compute improves static capability but does not close this train-deploy gap. We argue that addressing this limitation requires a new scaling axis-evolution. Existing deployment-time adaptation methods, whether parametric fine-tuning or heuristic memory accumulation, lack the strategic agency needed to diagnose failures and produce durable improvements. Our position is that agentic evolution represents the inevitable future of LLM adaptation, elevating evolution itself from a fixed pipeline to an autonomous evolver agent. We instantiate this vision in a general framework, A-Evolve, which treats deployment-time improvement as a deliberate, goal-directed optimization process over persistent system state. We further propose the evolution-scaling hypothesis: the capacity for adaptation scales with the compute allocated to evolution, positioning agentic evolution as a scalable path toward sustained, open-ended adaptation in the real world. Our code is publicly available at https://github.com/A-EVO-Lab/a-evolve.
From Agentification to Self-Evolving Agentic AI for Wireless Networks: Concepts, Approaches, and Future Research Directions
College of Computing and Data Science, Nanyang Technological University（计算与数据科学学院，南洋理工大学）；College of Computer Science and Technology, Jilin University（计算机科学与技术学院，吉林大学）；Department of Electrical and Computer Engineering, Western University（电气与计算机工程系，西方大学）；Department of Electrical and Computer Engineering, Auburn University（电气与计算机工程系，阿伯茨罕大学）；School of Electrical and Computer Engineering, University of Sydney（电气与计算机工程学院，悉尼大学）
EvoTrainer: Co-Evolving LLM Policies and Training Harnesses for Autonomous Agentic Reinforcement Learning
Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences（深圳先进技术研究院，中国科学院）；Tongyi Lab , Alibaba Group（通义实验室，阿里巴巴集团）；Alibaba Group（阿里巴巴集团）；SUAT（深圳大学）
TimeSage-EV: A Live Benchmark for Agentic Time Series Analysis in Evolving Environments
Eindhoven University of Technology（埃因霍温理工大学）；University of Oxford（牛津大学）；VulpiVox Intelligence（VulpiVox智能公司）；Squirrel Ai Learning（Squirrel AI学习公司）；Griffith University（格里菲斯大学）
HyEvo: Self-Evolving Hybrid Agentic Workflows for Efficient Reasoning
East China Normal University（华东师范大学）；Beihang University（北京航空航天大学）；Shanghai University of International Business and Economics（上海对外经贸大学）；Fudan University（复旦大学）
OctoT2I: A Self-Evolving Agentic Text-to-Image Router
School of Electronic and Computer Engineering, Peking University（电子与计算机工程学院，北京大学）；Guangdong Provincial Key Laboratory of Ultra High Definition Immersive Media Technology, Shenzhen Graduate School, Peking University（广东省超高清沉浸媒体技术重点实验室，北京大学深圳研究生院）
SAGE: A Self-Evolving Agentic Graph-Memory Engine for Structure-Aware Associative Memory
Institute for Artificial Intelligence, Peking University（北京大学人工智能研究院）；School of Intelligence Science and Technology, Peking University（北京大学智能科学与技术学校）；School of Computer Science and Technology, Beijing Institute of Technology（北京理工大学计算机科学与技术学校）
A Comprehensive Survey of Self-Evolving AI Agents: A New Paradigm Bridging Foundation Models and Lifelong Agentic Systems
University of Glasgow（格拉斯哥大学）；University of Sheffield（谢菲尔德大学）；Mohamed bin Zayed University of Artificial Intelligence（穆罕默德·本·扎耶德人工智能大学）；National University of Singapore（新加坡国家大学）；University of Cambridge（剑桥大学）；University College London（伦敦大学学院）；University of Aberdeen（阿伯丁大学）；Leiden University（莱顿大学）
MobEvolve: An Agentic Self-Evolving Heuristic System for Interpretable Human Mobility Generation
The Hong Kong Polytechnic University（香港理工大学）；McGill University（麦吉尔大学）；MIT（麻省理工学院）；Tsinghua University（清华大学）；Autorité régionale de transport métropolitain（大都会交通地区管理局）；Université de Montréal（蒙特利尔大学）；Mila – Quebec AI Institute（魁北克人工智能研究所）
LLMZ+: Contextual Prompt Whitelist Principles for Agentic LLMs
Department of Computer Science Mississippi State University（计算机科学系密苏里州立大学）；Department of Computer Science The University of Alabama（计算机科学系阿拉巴马大学）；Mississippi State University, Mississippi State, MS, USA（密苏里州立大学）；The University of Alabama, Tuscaloosa, AL, USA（阿拉巴马大学）
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）
Adapting to Evolving Requirements: Agentic AI for Retail Supply Chain Operations
School of Business and Management, Hong Kong University of Science and Technology（香港科技大学工商管理学院）；School of Management, University of Science and Technology of China（中国科学技术大学管理学院）；Institute of Operations Research and Analytics, National University of Singapore（新加坡国立大学运筹学与分析研究所）；NUS Business School, National University of Singapore（新加坡国立大学商学院）
AgenticSum: An Agentic Inference-Time Framework for Faithful Clinical Text Summarization
Department of XXX, University of YYY, Location, Country（XXX系，YYY大学，地点，国家）；School of ZZZ, Institute of WWW, Location, Country（ZZZ学院，WWW研究所，地点，国家）；University of Delaware, Newark, DE, USA（特拉华大学）
PhotoCraft: Agentic Reasoning with Hierarchical Self-Evolving Memory for Deep Image Search
Pattern Recognition Center, WeChat AI, Tencent Inc.（微信AI模式识别中心，腾讯公司）；Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；Zhongguancun Academy（中关村学院）；Nanyang Technological University（南洋理工大学）；Shanghai Jiao Tong University（上海交通大学）
LegoEnv: Self-Evolving Agentic Environments via Modular Recombination
Shanghai Jiao Tong University（上海交通大学）；Tencent（腾讯）；Emory University（埃默里大学）；National University of Singapore（新加坡国立大学）；Peking University（北京大学）；University of California, Santa Cruz（加州大学圣克鲁兹分校）
