Author

Jie Ma

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Preprint Oct 2026

Skill-V: Verifiable Self-Evolving Skill Library for Interactive Agents

Interactive agents can turn experience into reusable skills, yet existing self-evolving skill libraries primarily improve by accumulating new knowledge. Failures may lead to new skills, while previously stored skills are less often revisited as new evidence arrives. However, growth alone does not ensure reliability, as...

Jie Ma, Zhi-Peng Qian, Yu-Fei Ma et al. · 0 citations

#artificial intelligence Preprint Oct 2026

RAGStress: A controlled benchmark for evaluating retrieval-augmented generation under knowledge-base degradation

Retrieval-Augmented Generation (RAG) is typically evaluated under the implicit assumption that the underlying knowledge base (KB) is clean, leaving the behaviour of RAG systems under realistic KB degradation poorly characterised. We introduce RAGStress, a controlled evaluation benchmark for stress-testing RAG systems u...

Shi-Qi Yang, Jie Ma, Gao-Yuan Du · 0 citations

#artificial intelligence Preprint Sep 2026

Dr. Free: You Don't Need Difficulty Rewards for Self-Evolving Search Agents

This paper introduces \methodname, the first self-evolving search framework that eliminates difficulty-based proposer rewards and directly optimizes for evidence necessity relative to shortcut contexts, and shows that Dr. Free outperforms prior data-free search agents and the supervised baseline.

Zhi-Peng Qian, Zi-Han Liang, Yu-Fei Ma et al. · 0 citations