Fact, Fetch, and Reason: A Unified Evaluation of Retrieval-Augmented Generation · HackerPapers discussionshttps://hackerpaper.kaipfister.de/p/2409.12941/Collected HN comments and submissions linking this paper.enMon, 02 Nov 2026 11:16:22 GMTFact, Fetch, and Reason: A Unified Evaluation of Retrieval-Augmented Generation — mentioned by adg29https://news.ycombinator.com/item?id=41715745urn:hackerpapers:mention:2409.12941:41715745Tue, 01 Oct 2024 23:56:01 GMT<p>Evaluation dataset designed to test the capabilities of Retrieval-Augmented Generation (RAG) systems. Paper with details and experiments is available on arXiv: https://arxiv.org/abs/2409.12941. Dataset Overview 824 challenging multi-hop questions requiring information from 2-15 Wikipedia articles Questions span diverse topics including history, sports, science, animals, health, etc. Each question is labeled with reasoning types: numerical, tabular, multiple constraints, temporal, and post-processing Gold answers and relevant Wikipedia articles provided for each question Key Features Tests…</p><p><a href="https://hackerpaper.kaipfister.de/p/2409.12941/">Paper and discussion history</a>. A mention is not an endorsement.</p>cs.CL