An Iterative Utility Judgment Framework Inspired by Philosophical Relevance via LLMs (2026.findings-acl)
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| Challenge: | Relevance emphasizes the aboutness of a result to a query, while utility refers to the result’s usefulness or value to an information seeker. |
| Approach: | They propose an Iterative utiliTy judgmEnt fraMework to promote each step in Retrieval-Augmented Generation (RAG) they propose to use relevance ranking, utility judgments, and answer generation to prioritize high-utility results over low-utilitity results. |
| Outcome: | The proposed framework improves relevance, ranking, and answer generation on retrieval (TREC DL, WebAP), utility judgment task (GTI-NQ), and factoid question-answering (NQ) datasets. |
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