23 citations · 23 across the 4 of their papers we have counts for
4 papers
Revisiting Text Ranking in Deep Research
Chuan Meng, Litu Ou, Sean MacAvaney +1
Deep research has emerged as an important task that aims to address hard queries that need extensive open-web exploration. To tackle it, most prior work equips large language model…
Re-Rankers as Relevance Judges
Chuan Meng, Jiqun Liu, Mohammad Aliannejadi +3
Using large language models (LLMs) to predict relevance judgments has shown promising results. Most studies treat this task as a distinct research line, e.g., focusing on prompt de…
LLM-Evaluation Tropes: Perspectives on the Validity of LLM-Evaluations
Laura Dietz, Oleg Zendel, Peter Bailey +6
Large Language Models (LLMs) are increasingly used to evaluate information retrieval (IR) systems, generating relevance judgments traditionally made by human assessors. Recent empi…
Induced Natural Language Rationales and Interleaved Markup Tokens Enable Extrapolation in Large Language Models
Mirelle Bueno, Carlos Gemmell, Jeffrey Dalton +2
The ability to extrapolate, i.e., to make predictions on sequences that are longer than those presented as training examples, is a challenging problem for current deep learning mod…