9 citations · 21 across the 7 of their papers we have counts for
4 papers · 1 filter
Initial Nugget Evaluation Results for the TREC 2024 RAG Track with the AutoNuggetizer Framework
Ronak Pradeep, Nandan Thakur, Shivani Upadhyay +3
This report provides an initial look at partial results from the TREC 2024 Retrieval-Augmented Generation (RAG) Track. We have identified RAG evaluation as a barrier to continued p…
A Large-Scale Study of Relevance Assessments with Large Language Models: An Initial Look
Shivani Upadhyay, Ronak Pradeep, Nandan Thakur +5
The application of large language models to provide relevance assessments presents exciting opportunities to advance information retrieval, natural language processing, and beyond,…
Ragnarök: A Reusable RAG Framework and Baselines for TREC 2024 Retrieval-Augmented Generation Track
Ronak Pradeep, Nandan Thakur, Sahel Sharifymoghaddam +5
Did you try out the new Bing Search? Or maybe you fiddled around with Google AI~Overviews? These might sound familiar because the modern-day search stack has recently evolved to in…
Synthetic Test Collections for Retrieval Evaluation
Hossein A. Rahmani, Nick Craswell, Emine Yilmaz +2
Test collections play a vital role in evaluation of information retrieval (IR) systems. Obtaining a diverse set of user queries for test collection construction can be challenging,…