From the 3 of 27 linked papers with an AI index.
27 papers
Rethinking Self-Evolving Agent Skills: Feedback Dynamics over Multiple Rounds
Yuxuan Liu, Zhaochen Su, Yuhao Zhang +9
Self-evolving skill systems promise to improve agents by turning execution feedback into persistent skill updates without changing the underlying model. Yet it remains unclear when…
RLPF: Reinforcement Learning from Performance Feedback for Code Generation
Huihao Jing, Haozhe Cui, Wenbin Hu +9
The paper introduces RLPF, a reinforcement‑learning approach that uses staged performance feedback to train code‑generation models to produce not only correct programs but also fas…
Isolation as a First-Class Principle for LLM-Agent System Safety: Concepts, Taxonomy, Challenges and Future Directions
Huihao Jing, Wenbin Hu, Shaojin Chen +10
The paper surveys how isolating components such as user inputs, tools, execution, inter‑agent communication, and environment can improve safety of LLM‑agent systems, presenting a b…
PerfCodeBench: Benchmarking LLMs for System-Level High-Performance Code Optimization
Huihao Jing, Wenbin Hu, Shaojin Chen +5
The paper introduces PerfCodeBench, an executable benchmark that evaluates how well large language models can generate system-level code that is not only correct but also optimized…
SkillRevise: Improving LLM-Authored Agent Skills via Trace-Conditioned Skill Revision
Yuxuan Liu, Zhaochen Su, Lingyun Xie +11
Agent skills are procedural artifacts that enable LLM agents to execute workflows, verify constraints, and recover from failures. Existing self-evolving methods refine skills using…
Steering LLM Viewpoints through Fabricated Evidence Injection
Xi Yang, Chang Liu, Zhenglin Huang +4
As chatbots increasingly influence daily decision-making, their potential to produce misleading responses poses substantial risks to users. This paper investigates a critical cogni…