arXiv AI
Beyond Top-$k$ Skill Retrieval: Diversity-Aware Skill Routing for LLM Agents
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arXiv AI
3d ago
SkillContrast: Difference-Guided Text Selection for Agent Skill Reranking
SkillContrast is a training‑free selector that compares retrieved agent skills and keeps only the text that differs between them, preserving local context for a pretrained reranker. In experiments on 1,235 requests from SameCapRisk‑Bench, it improves clean‑hit rates by 54–72 over TF‑IDF query selection while using 51.1–58.8% fewer input tokens. The method shows that retaining differing text, rather than full skill bodies, is the key factor for better reranking performance.
arXiv Computation and Language
4d ago
Finding the Right Balance: Relevance and Diversity in LLM Retrieval
arXiv:2610.09412v1 Announce Type: cross Abstract: Retrieval diversification is widely available in retrieval-augmented generation (RAG) frameworks, yet prior studies disagree on whether it improves r...
arXiv AI
Sep 1
SkillRet: A Large-Scale Benchmark for Skill Retrieval in LLM Agents
arXiv:2605.05726v2 Announce Type: replace Abstract: As LLM agents are increasingly deployed with large libraries of reusable skills, selecting the right skill for a user request has become a critical...
Hugging Face Trending Papers
5d ago
Finding the Right Balance: Relevance and Diversity in LLM Retrieval
Retrieval diversification is widely available in retrieval-augmented generation (RAG) frameworks, yet prior studies disagree on whether it improves retrieval and answer quality. We show that its effec...
arXiv AI
Jul 22
SkillSight: Seeing Through Shared Descriptions for Accurate Skill Retrieval
arXiv:2607. 18785v1 Announce Type: new Abstract: As large language model agents gain access to increasingly large skill libraries, retrieving the right skill becomes critical to reliable capability selection and execution.
arXiv AI
Jul 31
SkillSight: Calibrating Generic Content Bias for Skill Retrieval
arXiv:2607. 18785v2 Announce Type: replace Abstract: As large language model agents gain access to increasingly large skill libraries, retrieving the right skill becomes critical to reliable capability selection and execution.