9 citations · 11 across the 9 of their papers we have counts for
3 papers · 1 filter
MoR: Better Handling Diverse Queries with a Mixture of Sparse, Dense, and Human Retrievers
Jushaan Singh Kalra, Xinran Zhao, To Eun Kim +3
Retrieval-augmented Generation (RAG) is powerful, but its effectiveness hinges on which retrievers we use and how. Different retrievers offer distinct, often complementary signals:…
Towards Fair RAG: On the Impact of Fair Ranking in Retrieval-Augmented Generation
To Eun Kim, Fernando Diaz
Despite the central role of retrieval in retrieval-augmented generation (RAG) systems, much of the existing research on RAG overlooks the well-established field of fair ranking and…
Overview of the TREC 2019 Fair Ranking Track
Asia J. Biega, Fernando Diaz, Michael D. Ekstrand +1
The goal of the TREC Fair Ranking track was to develop a benchmark for evaluating retrieval systems in terms of fairness to different content providers in addition to classic notio…