From Knowledge Access to Source Learning: Developing Source-Specific Competence

Lucheng Fu, Kejing Xia, Yiyang Wang, Yiqiao Jin, Jinjin He et al.|October 1, 2026arXiv

Key Takeaway

LLM agents can significantly improve performance on knowledge-intensive tasks by learning persistent, source-specific models that evolve through repeated interaction—achieving up to 22.6 point gains over standard retrieval methods.

Summary

This paper introduces SourceLearn, a method for LLM agents to develop persistent, reusable understanding of external knowledge sources through repeated interaction.

training agents reasoning

Key Terms

rag-pipeline source-model agentic-language-model