Agent Skill Learning

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24 papers in the last four weeks, up 200% on the four weeks before. 0.2% of all new papers.

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Latest papers 123

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Skill-as-Pseudocode: Refactoring Skill Libraries to Pseudocode for LLM Agents
May 27, 2026Xinze Li, Yuhang Zang, Yixin Cao +1Tool-Augmented Language Model Agents LLM Agent Skill Retrieval
Nanyang Technological University · Shanghai AI Laboratory · Fudan University
Exploiting Local Dynamics Regularity for Reusable Skills in Offline Hierarchical RL
May 25, 2026Sarthak Dayal, Abhinav Peri, Carl Qi +4Hierarchical RL Offline RL
Department of Computer Science University of Texas at Austin · UT Austin · OpenAI
Partner-Aware Hierarchical Skill Discovery for Robust Human-AI Collaboration
May 23, 2026Adnan Ahmad, Bahareh Nakisa, Mohammad Naim RastgooHierarchical RL Multi-Agent Collaboration
aSchoold of Information Technology, Deakin University, 75 Pidgons Rd, Waurn Ponds, 3216, VIC, Australia · bFaculty of Information Technology, Monash University, Wellington Rd, Clayton, 3800, VIC, Australia
Adaptive Human-AI Coordination via Hierarchical Action Disentanglement
May 23, 2026Adnan Ahmad, Bahareh Nakisa, Mohammad Naim RastgooDisentangled Representation Learning Hierarchical RL
School of Information Technology Deakin University, Waurn Ponds, 3216, VIC, Australia · Faculty of Information Technology, Monash University, 3800, VIC, Australia
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
SkillOpt: Executive Strategy for Self-Evolving Agent Skills
May 22, 2026Yifan Yang, Ziyang Gong, Weiquan Huang +12Large Language Model-Guided Optimization LLM Agent Self-Improvement
Microsoft · Shanghai Jiao Tong University · Tongji University +1
From Correctness to Preference: A Framework for Personalized Agentic Reinforcement Learning
May 22, 2026Ranxu zhang, zeyang li, Jiacheng Huang +5Agentic RL Reinforcement Learning
University of Science and Technology of China · Alibaba Group
Residual Skill Optimization for Text-to-SQL Ensembles
May 20, 2026Jiongli Zhu, Haoquan Guan, Parjanya Prajakta Prashant +8Text-to-SQL Agent Skill Learning
University of California, San Diego · 2Snowflake AI Research
Terminal-World: Scaling Terminal-Agent Environments via Agent Skills
May 20, 2026Zihao Cheng, Hongru Wang, Zeming Liu +6Tool-Augmented Language Model Agents Terminal Agents
School of Computer Science and Engineering, Beihang University, Beijing, China · Independent Researcher · 3Beijing Institute of Technology +2
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
EmbodiSkill: Skill-Aware Reflection for Self-Evolving Embodied Agents
May 11, 2026Ruofei Ju, Xinrui Wang, Xin Ding +12LLM Agent Skill Learning Agent Skill Learning
Nanjing University · Institute for AI Industry Research (AIR), Tsinghua University · Huazhong University of Science and Technology +2
Kintsugi: Learning Policies by Repairing Executable Knowledge Bases
May 10, 2026Teng Cao, Yu Deng, Hikaru Shindo +6Robot Policy Learning LLM Agent Self-Improvement
Artificial Intelligence and Machine Learning Lab, Technical University of Darmstadt, Germany · Hessian Center for Artificial Intelligence (hessian.AI), Germany · Department of Computer Science, Technical University of Darmstadt, Germany +6
Skill-R1: Agent Skill Evolution via Reinforcement Learning
May 10, 2026Yash Vishe, Rohan Surana, Xunyi Jiang +8Agent Skill Learning RL for LLM Agents
UC San Diego · Adobe Research
Evidence Over Plans: Online Trajectory Verification for Skill Distillation
May 9, 2026Yang Zhou, Zihan Dong, Zhenting Wang +7Agent Evaluation Agent Skill Learning
Rutgers University
Ace-Skill: Bootstrapping Multimodal Agents with Prioritized and Clustered Evolution
May 9, 2026Feng Xiong, Zengbin Wang, Yong Wang +5Continual Learning for LLM Agents Agent Skill Learning
1AMAP, Alibaba Group · 2CASIA · 3BNU
Unifying Goal-Conditioned RL and Unsupervised Skill Learning via Control-Maximization
May 7, 2026Alireza Modirshanechi, Benjamin Eysenbach, Peter Dayan +1Reinforcement Learning Agent Skill Learning
Helmholtz Munich, Germany · Max Planck Institute for Biological Cybernetics, Germany · Princeton University, USA +1
LineRides: Line-Guided Reinforcement Learning for Bicycle Robot Stunts
May 6, 2026Seungeun Rho, Shamel Fahmi, Jeonghwan Kim +3Reinforcement Learning Robot Skill Learning
1RAI Institute, Cambridge, MA, USA · Georgia Institute of Technology, Atlanta, GA, USA
From Context to Skills: Can Language Models Learn from Context Skillfully?
Apr 30, 2026Shuzheng Si, Haozhe Zhao, Yu Lei +10In-Context Learning Agent Skill Learning
THU · UIUC · DeepLang AI +2
Bian Que: An Agentic Framework with Flexible Skill Arrangement for Online System Operations
Apr 29, 2026Bochao Liu, Zhipeng Qian, Yang Zhao +10Continual Learning for LLM Agents LLM Agent Orchestration
Kuaishou Technology
DRIVE: Modeling Skills at the Reasoning and Interaction Levels for Web Agents under Continual Learning
Apr 28, 2026Xirui Liu, Sihang Zhou, Yanning Hou +6Continual Learning for LLM Agents LLM Agent Skill Learning
College of Intelligence Science and Technology, National University of Defense Technology, Changsha, 410073, Hunan, China · College of Computer Science and Technology, National University of Defense Technology, Changsha, 410073, Hunan, China
Leveraging Human Feedback for Semantically-Relevant Skill Discovery
Apr 27, 2026Maxence Hussonnois, Thommen George Karimpanal, Santu RanaAgent Skill Learning RL from Human Feedback
A2I2, Deakin University, Geelong, Australia · School of IT, Deakin University, Geelong, Australia.
ALAS: Adaptive Long-Horizon Action Synthesis via Async-pathway Stream Disentanglement
Apr 22, 2026Yutong Shen, Hangxu Liu, Lei Zhang +4Disentangled Representation Learning Cross-Domain Transfer Learning
Beijing University of Technology · Fudan University · University of Hamburg +2
SkillLearnBench: Benchmarking Continual Learning Methods for Agent Skill Generation on Real-World Tasks
Apr 22, 2026Shanshan Zhong, Yi Lu, Jingjie Ning +7Continual Learning for LLM Agents LLM Agent Evaluation
Carnegie Mellon University · Amazon AGI
SkillGraph: Self-Evolving Multi-Agent Collaboration with Multimodal Graph Topology
Apr 19, 2026Zheng Nie, Ruolin Shen, Xinlei Yu +3Multi-Agent Collaboration Dynamic Graph Learning
National University of Singapore, Singapore · Technical University of Munich, Munich, Germany · Zhejiang University, China
SkillFlow:Benchmarking Lifelong Skill Discovery and Evolution for Autonomous Agents
Apr 19, 2026Ziao Zhang, Kou Shi, Shiting Huang +13Lifelong Learning Agents Long-Horizon Agent Evaluation
University of Science and Technology of China · University of Toronto · University of Sydney
TRACE: Capability-Targeted Agentic Training
Apr 7, 2026Hangoo Kang, Tarun Suresh, Jon Saad-Falcon +1LLM Agent Self-Improvement Agent Skill Learning
Stanford University
ASDA: Automated Skill Distillation and Adaptation for Financial Reasoning
Mar 17, 2026Tik Yu Yim, Wenting Tan, Sum Yee Chan +2Domain Adaptation for LLMs Agent Skill Learning
The University of Hong Kong, Hong Kong SAR, China
XSkill: Continual Learning from Experience and Skills in Multimodal Agents
Mar 12, 2026Guanyu Jiang, Zhaochen Su, Xiaoye Qu +1Agent Skill Learning Multimodal Agents
Hong Kong University of Science and Technology · Zhejiang University · Huazhong University of Science and Technology
Evolving Programmatic Skill Networks
Jan 7, 2026Haochen Shi, Xingdi Yuan, Bang LiuContinual Learning for LLM Agents LLM-Based Program Synthesis
DIRO & Institut Courtois, Université de Montréal · Mila – Québec AI Institute · Microsoft Research +1

May 27, 2026, cs.PLJ/K move · Enter open · S save

Skill-as-Pseudocode: Refactoring Skill Libraries to Pseudocode for LLM Agents

Xinze Li, Yuhang Zang, Yixin Cao, Aixin Sun

Nanyang Technological University · Shanghai AI Laboratory · Fudan University

Tool-Augmented Language Model Agents LLM Agent Skill Retrieval LLM Agents Agent Skill Learning

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Markdown skill libraries for LLM agents ship as free-form prose, forcing the agent to re-derive both the input schema and the concrete invocation syntax on every retrieval. This produces a "confused

\to

re-retrieve

\to

still confused" loop: the agent issues a partially-correct action, receives uninformative feedback, and re-retrieves the same prose. We propose Skill-as-Pseudocode (SaP), an automatic conversion of markdown skill libraries into typed pseudocode with deterministic quality control. From each cluster of similar procedural passages, SaP extracts a typed contract and filters it through a four-check deterministic verifier (coverage, binding, replacement, risk). Promoted contracts are inlined into a rewritten skill skeleton alongside restored action templates, giving the agent two complementary signals: a typed signature for what a skill does and a concrete template for how to invoke it. On the ALFWorld unseen split (134 games, gpt-4o-mini, three seeds), SaP wins 82/402 paired games versus 47/402 for the Graph-of-Skills (GoS) baseline (pooled McNemar

p = 8.2 \times 10^{-5}

), at

-22.8 \pm 6.4

% input tokens and

-14.5 \pm 4.1

% LLM calls per game. A bundle-component ablation attributes the gain to the pairing of typed contracts with concrete action templates: the contract alone falls below the prose baseline.

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Latest papers 123