arXiv cs.CL
· Papers
Beyond Relevance-Centric Retrieval: Rubric-Oriented Document Set Selection and Ranking
arXiv:2607.19747v1 Announce Type: new Abstract: As large language models and AI agents become the primary consumers of search results, document set quality determines the upper bound of downstream generation. Yet existing evaluation systems remain confined to scoring documents independently and aggregating via nDCG, ig