LLM Agent Skill Learning

LLM: Large Language Model

This field asks how language-model agents can turn experience, demonstrations, external guides, or feedback into reusable procedures for tasks such as tool use, web navigation, coding, and embodied control. Common approaches distill skills from successful and failed trajectories into text, executable programs, or hierarchical libraries, then retrieve, compose, verify, and revise them; other methods train agents to internalize skills through supervised fine-tuning or reinforcement learning. Work is evaluated on interactive benchmarks such as ALFWorld, WebShop, AppWorld, and coding tasks, with attention to success, transfer, token cost, and consistency. A central challenge is that skills can help when relevant but cause regressions when stale, poorly selected, or applied outside their scope, making reliable validation, lifecycle management, and safety essential.

Latest papers

402 papers71 papers in the last four weeks, up 39% on the four weeks before. 0.4% of all new papers.

ESC-Skills: Discovering and Self-Evolving Skills for Emotional Support Conversations
May 27, 2026Jie Zhu, Huaixia Dou, Shuo Jiang +5Emotional Support Conversation LLM Agent Skill Learning
School of Computer Science and Technology, Soochow University · 2Qwen DianJin Team, Alibaba Cloud Computing
SKILLC: Learning Autonomous Skill Internalization in LLM Agents via Contrastive Credit Assignment
May 27, 2026Hongxiang Lin, Zhirui Kuai, Erpeng Xue +1LLM Agent Skill Learning Credit Assignment
Meituan
SkillGrad: Optimizing Agent Skills Like Gradient Descent
May 26, 2026Hanyu Wang, Yifan Lan, Bochuan Cao +2Large Language Model-Guided Optimization LLM Agent Self-Improvement
College of Information Sciences and Technology The Pennsylvania State University University Park, PA, USA
MUSE-Autoskill: Self-Evolving Agents via Skill Creation, Memory, Management, and Evaluation
May 26, 2026Huawei Lin, Peng Li, Jie Song +2LLM Agent Skill Learning LLM Agent Skill Retrieval
ByteDance Inc.
EmoDistill: Offline Emotion Skill Distillation for Language Model Agents in Adversarial Negotiation
May 26, 2026Yunbo Long, Haolang Zhao, Lukas Beckenbauer +2Multi-Agent Negotiation Automated Negotiation
University of Cambridge · Technical University of Munich · Exiger LLC +1
Verilog-Evolve: Feedback-Driven and Skill-Evolving Verilog Generation
May 26, 2026Zehua Pei, Hui-Ling Zhen, Yu Zhang +3Large Language Model-Guided Optimization Execution-Guided Code Generation
The Chinese University of Hong Kong · Huawei Technologies Co., Ltd
When Search Becomes Memory: Accelerating Robot Design Discovery with Self-Evolving Skills
May 25, 2026Yunfei Wang, Xiaohao Xu, Yang Li +1Robotics LLM Agent Skill Learning
University of Michigan, Ann Arbor
SetupX: Can LLM Agents Learn from Past Failures in Functionality-Correct Code Repository Setup?
May 25, 2026Zihang Zhou, Ziqian Ren, Yukai Wu +7Software Engineering Agents LLM Agent Self-Improvement
Shanghai Jiao Tong University · Beijing University of Posts and Telecommunications · Independent Researcher +2
CODESKILL: Learning Self-Evolving Skills for Coding Agents
May 25, 2026Yanzhou Li, Yiran Zhang, Xiaoyu Zhang +2Coding Agents LLM Agent Skill Learning
Nanyang Technological University · 2Zhejiang University
PANDO: Efficient Multimodal AI Agents via Online Skill Distillation
May 24, 2026Yubo Li, Yidi Miao, Yuntian Shen +1LLM Agent Workflow Optimization LLM Agent Skill Learning
SkillEvolBench: Benchmarking the Evolution from Episodic Experience to Procedural Skills
May 22, 2026Yingtie Lei, Zhongwei Wan, Jiankun Zhang +13LLM Agent Evaluation LLM Agent Skill Learning
1The Ohio State University · 2The University of Chicago · University College London +4
From Raw Experience to Skill Consumption: A Systematic Study of Model-Generated Agent Skills
May 22, 2026Zisu Huang, Jingwen Xu, Yifan Yang +13LLM Agent Evaluation LLM Agent Skill Learning
Fudan University · Microsoft Research · Shanghai Jiao Tong University
More Skills, Worse Agents? Skill Shadowing Degrades Performance When Expanding Skill Libraries
May 21, 2026Hongwen Song, Song WeiLLM Agent Evaluation LLM Agent Skill Learning
Databricks Inc.
Ratchet: A Minimal Hygiene Recipe for Self-Evolving LLM Agents
May 21, 2026Xing Zhang, Yanwei Cui, Guanghui Wang +4Continual Learning for LLM Agents LLM Agent Self-Improvement
AWS Generative AI Innovation Center · HSBC Holdings Plc., HSBC Technology Center, China
Trace2Skill: Verifier-Guided Skill Evolution for Long-Context EDA Agents
May 20, 2026Zijian Du, Nathaniel PinckneyElectronic Design Automation Code Generation
NVIDIA · Santa Clara, CA, USA
When Skills Don't Help: A Negative Result on Procedural Knowledge for Tool-Grounded Agents in Offensive Cybersecurity
May 19, 2026Samuel Jacob Chacko, James Hugglestone, Chashi Mahiul Islam +1LLM Agent Evaluation LLM Agent Skill Learning
Florida State University, Tallahassee, Florida, USA
A Case for Agentic Tuning: From Documentation to Action in PostgreSQL
May 19, 2026Hongyu Lin, Mingyu Li, Weichen Zhang +4Large Language Model-Guided Optimization LLM Agent Skill Learning
Institute of Software, Chinese Academy of Sciences · University of Chinese Academy of Sciences · Key Laboratory of System Software (Chinese Academy of Sciences) +3
Library Drift: Diagnosing and Fixing a Silent Failure Mode in Self-Evolving LLM Skill Libraries
May 19, 2026Xing Zhang, Yanwei Cui, Guanghui Wang +4Continual Learning for LLM Agents LLM Agent Self-Improvement
1AWS Generative AI Innovation Center · 2HSBC Holdings Plc., HSBC Technology Center, China.
MOCHA: Multi-Objective Chebyshev Annealing for Agent Skill Optimization
May 19, 2026Md Mehrab Tanjim, Jayakumar Subramanian, Branislav Kveton +6LLM Agent Skill Learning Multi-Objective Optimization
Adobe Research
SkillGenBench: Benchmarking Skill Generation Pipelines for LLM Agents
May 18, 2026Yifan Zhou, Zhentao Zhang, Ziming Cheng +8LLM Agent Evaluation LLM Agent Skill Learning
1SJTU · 2XJTU · 3NUS +6
SkillsVote: Lifecycle Governance of Agent Skills from Collection, Recommendation to Evolution
May 18, 2026Hongyi Liu, Haoyan Yang, Tao Jiang +4AI Coding Agents LLM Agent Skill Learning
1MemTensor (Shanghai) Technology · 2Harbin Institute of Technology · 3Soochow University +1
Harnessing LLM Agents with Skill Programs
May 18, 2026Hongjun Liu, Yifei Ming, Shafiq Joty +1LLM Agent Self-Improvement LLM Agent Skill Learning
New York University · Salesforce AI Research
Skills on the Fly: Test-Time Adaptive Skill Synthesis for LLM Agents
May 16, 2026Jingxing Wang, Chenyu Zhou, Zhihui Fu +4Test-Time Adaptation LLM Agent Skill Learning
1Shanghai Jiao Tong University · 2OPPO Research Institute
Good to Go: The LOOP Skill Engine That Hits 99% Success and Slashes Token Usage by 99% via One-Shot Recording and Deterministic Replay
May 14, 2026Xiaohua Wang, Kai Yu, XuXiao Liang +2LLM Inference Efficiency AI Agent Reliability
1Artificial Intelligence Research Center, Bengbu Medical University, Bengbu 233000, China. · 2CHARMMIRAEL Biotech Co., Ltd, Nanjing 210000, China.
SkillFlow: Flow-Driven Recursive Skill Evolution for Agentic Orchestration
May 13, 2026Mingda Zhang, Tiesunlong Shen, Haoran Luo +4LLM Agent Orchestration LLM Agent Self-Improvement
The Chinese University of Hong Kong, Shenzhen · National University of Singapore · Nanyang Technological University +1
MMSkills: Towards Multimodal Skills for General Visual Agents
May 13, 2026Kangning Zhang, Shuai Shao, Qingyao Li +8GUI Agents LLM Agent Skill Learning
1Shanghai Jiao Tong University · 2Xiaohongshu Inc. · 3Southeast University
SkillGraph: Skill-Augmented Reinforcement Learning for Agents via Evolving Skill Graphs
May 12, 2026Xiaoyuan Li, Moxin Li, Keqin Bao +4LLM Agent Skill Learning LLM Agent Skill Retrieval
University of Science and Technology of China · National University of Singapore · Alibaba Group
Dynamic Skill Lifecycle Management for Agentic Reinforcement Learning
May 11, 2026Junhao Shen, Teng Zhang, Xiaoyan Zhao +1Agentic RL LLM Agent Skill Learning
Database Group, The Chinese University of Hong Kong · Lanzhou University
NanoResearch: Co-Evolving Skills, Memory, and Policy for Personalized Research Automation
May 11, 2026Jinhang Xu, Qiyuan Zhu, Yujun Wu +11Multi-Agent LLM Systems LLM Agent Skill Learning
1Shanghai Artificial Intelligence Laboratory · 2The Hong Kong University of Science and Technology · 3Peking University +4
SkillEvolver: Skill Learning as a Meta-Skill
May 11, 2026Genrui Zhang, Erle Zhu, Jinfeng Zhou +2LLM Agent Self-Improvement LLM Agent Skill Learning
2Beijing Jiaotong University · 1Tsinghua University

May 27, 2026J/K move · Enter open · S save

ESC-Skills: Discovering and Self-Evolving Skills for Emotional Support Conversations

Jie Zhu, Huaixia Dou, Shuo Jiang, Junhui Li+4

School of Computer Science and Technology, Soochow University · 2Qwen DianJin Team, Alibaba Cloud Computing

Emotional Support Conversation LLM Agent Skill Learning Self-Evolving Agents

Open paper AskPDF arXiv

Existing emotional support conversation (ESC) systems mainly rely on end-to-end response generation or coarse strategy supervision, offering limited interpretability and little support for systematic skill improvement. We propose ESC-Skills, a skill-centric framework that discovers and self-evolves executable emotional support skills. We first model localized support interactions as Intervention Units (IUs), which capture state--action--outcome dynamics between seeker states, support interventions, and post-response emotional changes. Based on IUs extracted from both successful and failed ESC dialogues, we construct the ESC-Skills Bank, a repository of executable emotional support skills containing intervention guidance, applicability conditions, expected outcomes, and potential risks. To further improve robustness, we introduce a multi-profile self-evolutionary refinement framework in which an ESC agent interacts with diverse simulated seeker profiles under SAGE evaluation. The resulting interaction traces are analyzed to identify missing skills, unsafe interventions, and profile-specific failure patterns, which are then used to refine the Skills Bank through simulation-based verification. Experimental results demonstrate that ESC-Skills improves both response-level quality and dialogue-level emotional outcomes while providing more interpretable and controllable support behaviors. We will release the code, prompts, and ESC-Skills Bank at https://github.com/aliyun/qwen-dianjin.