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Match Your Words! A Study of Lexical Matching in Neural Information
  Retrieval
v1v2 (latest)

Match Your Words! A Study of Lexical Matching in Neural Information Retrieval

10 December 2021
Thibault Formal
Benjamin Piwowarski
Stéphane Clinchant
ArXiv (abs)PDFHTML

Papers citing "Match Your Words! A Study of Lexical Matching in Neural Information Retrieval"

5 / 5 papers shown
Title
How do Large Language Models Understand Relevance? A Mechanistic Interpretability Perspective
How do Large Language Models Understand Relevance? A Mechanistic Interpretability Perspective
Qi Liu
Jiaxin Mao
Ji-Rong Wen
LRM
79
1
0
10 Apr 2025
When do Generative Query and Document Expansions Fail? A Comprehensive
  Study Across Methods, Retrievers, and Datasets
When do Generative Query and Document Expansions Fail? A Comprehensive Study Across Methods, Retrievers, and Datasets
Orion Weller
Kyle Lo
David Wadden
Dawn J Lawrie
Benjamin Van Durme
Arman Cohan
Luca Soldaini
87
21
0
15 Sep 2023
Can a Frozen Pretrained Language Model be used for Zero-shot Neural
  Retrieval on Entity-centric Questions?
Can a Frozen Pretrained Language Model be used for Zero-shot Neural Retrieval on Entity-centric Questions?
Yasuto Hoshi
Daisuke Miyashita
Yasuhiro Morioka
Youyang Ng
Osamu Torii
J. Deguchi
65
0
0
09 Mar 2023
Unsupervised Domain Adaptation for Sparse Retrieval by Filling
  Vocabulary and Word Frequency Gaps
Unsupervised Domain Adaptation for Sparse Retrieval by Filling Vocabulary and Word Frequency Gaps
Hiroki Iida
Naoaki Okazaki
80
5
0
08 Nov 2022
From Distillation to Hard Negative Sampling: Making Sparse Neural IR
  Models More Effective
From Distillation to Hard Negative Sampling: Making Sparse Neural IR Models More Effective
Thibault Formal
Carlos Lassance
Benjamin Piwowarski
Stéphane Clinchant
VLM
101
149
0
10 May 2022
1