25 citations · 133 across the 34 of their papers we have counts for
16 papers · 1 filter
Which Neurons Matter in IR? Applying Integrated Gradients-based Methods to Understand Cross-Encoders
Mathias Vast, Basile Van Cooten, Laure Soulier +1
With the recent addition of Retrieval-Augmented Generation (RAG), the scope and importance of Information Retrieval (IR) has expanded. As a result, the importance of a deeper under…
Simple Domain Adaptation for Sparse Retrievers
Mathias Vast, Yuxuan Zong, Basile Van Cooten +2
In Information Retrieval, and more generally in Natural Language Processing, adapting models to specific domains is conducted through fine-tuning. Despite the successes achieved by…
Query Performance Prediction for Neural IR: Are We There Yet?
Guglielmo Faggioli, Thibault Formal, Stefano Marchesin +3
Evaluation in Information Retrieval relies on post-hoc empirical procedures, which are time-consuming and expensive operations. To alleviate this, Query Performance Prediction (QPP…
CoSPLADE: Contextualizing SPLADE for Conversational Information Retrieval
Nam Le Hai, Thomas Gerald, Thibault Formal +3
Conversational search is a difficult task as it aims at retrieving documents based not only on the current user query but also on the full conversation history. Most of the previou…
From Distillation to Hard Negative Sampling: Making Sparse Neural IR Models More Effective
Thibault Formal, Carlos Lassance, Benjamin Piwowarski +1
Neural retrievers based on dense representations combined with Approximate Nearest Neighbors search have recently received a lot of attention, owing their success to distillation a…
Match Your Words! A Study of Lexical Matching in Neural Information Retrieval
Thibault Formal, Benjamin Piwowarski, Stéphane Clinchant
Neural Information Retrieval models hold the promise to replace lexical matching models, e.g. BM25, in modern search engines. While their capabilities have fully shone on in-domain…