47 citations · 94 across the 4 of their papers we have counts for
4 papers · 1 filter
TREC iKAT 2023: The Interactive Knowledge Assistance Track Overview
Mohammad Aliannejadi, Zahra Abbasiantaeb, Shubham Chatterjee +2
Conversational Information Seeking has evolved rapidly in the last few years with the development of Large Language Models providing the basis for interpreting and responding in a…
DREQ: Document Re-Ranking Using Entity-based Query Understanding
Shubham Chatterjee, Iain Mackie, Jeff Dalton
While entity-oriented neural IR models have advanced significantly, they often overlook a key nuance: the varying degrees of influence individual entities within a document have on…
Generative and Pseudo-Relevant Feedback for Sparse, Dense and Learned Sparse Retrieval
Iain Mackie, Shubham Chatterjee, Jeffrey Dalton
Pseudo-relevance feedback (PRF) is a classical approach to address lexical mismatch by enriching the query using first-pass retrieval. Moreover, recent work on generative-relevance…
Generative Relevance Feedback with Large Language Models
Iain Mackie, Shubham Chatterjee, Jeffrey Dalton
Current query expansion models use pseudo-relevance feedback to improve first-pass retrieval effectiveness; however, this fails when the initial results are not relevant. Instead o…