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

15 September 2023

Kyle Lo

Benjamin Van Durme

Arman Cohan

Luca Soldaini

Papers citing "When do Generative Query and Document Expansions Fail? A Comprehensive Study Across Methods, Retrievers, and Datasets"

10 / 10 papers shown

Title
NevIR: Negation in Neural Information Retrieval Orion Weller Dawn J Lawrie Benjamin Van Durme MU 49 18 0 12 May 2023
Query2doc: Query Expansion with Large Language Models Liang Wang Nan Yang Furu Wei 88 97 0 14 Mar 2023
Rethinking with Retrieval: Faithful Large Language Model Inference Hangfeng He Hongming Zhang Dan Roth KELM LRM 141 151 0 31 Dec 2022
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models Jason W. Wei Xuezhi Wang Dale Schuurmans Maarten Bosma Brian Ichter F. Xia Ed H. Chi Quoc Le Denny Zhou LM&Ro LRM AI4CE ReLM 315 8,261 0 28 Jan 2022
Salient Phrase Aware Dense Retrieval: Can a Dense Retriever Imitate a Sparse One? Xilun Chen Kushal Lakhotia Barlas Oğuz Anchit Gupta Patrick Lewis Stanislav Peshterliev Yashar Mehdad Sonal Gupta Wen-tau Yih 48 67 0 13 Oct 2021
SPLADE v2: Sparse Lexical and Expansion Model for Information Retrieval Thibault Formal Carlos Lassance Benjamin Piwowarski S. Clinchant 194 184 0 21 Sep 2021
BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models Nandan Thakur Nils Reimers Andreas Rucklé Abhishek Srivastava Iryna Gurevych VLM 229 961 0 17 Apr 2021
Overview of the TREC 2020 deep learning track Nick Craswell Bhaskar Mitra Emine Yilmaz Daniel Fernando Campos 54 362 0 15 Feb 2021
Pretrained Transformers for Text Ranking: BERT and Beyond Jimmy J. Lin Rodrigo Nogueira Andrew Yates VLM 214 607 0 13 Oct 2020
Overview of the TREC 2019 deep learning track Nick Craswell Bhaskar Mitra Emine Yilmaz Daniel Fernando Campos E. Voorhees 174 453 0 17 Mar 2020