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20242026
most citedWhich Neurons Matter in IR? Applying Integrated Gradients-based Methods to Understand Cross-Encoders

2 citations · 3 across the 5 of their papers we have counts for

collaborators

7 papers

cs.IR2026

MICE to Meet You: From Re-ranking Only to End-to-End Retrieval

Victor Morand, Yuxuan Zong, Mathias Vast +2

Late-interaction models offer state-of-the-art efficiency-effectiveness trade-offs for neural retrieval by enabling document representations to be pre-computed and efficiently inde…

cs.IR2026

From Tokens to Concepts: Leveraging SAE for SPLADE

Yuxuan Zong, Mathias Vast, Basile Van Cooten +2

Learned Sparse IR models, such as SPLADE, offer an excellent efficiency-effectiveness tradeoff. However, they rely on the underlying backbone vocabulary, which might hinder perform…

cs.IR2026

Building Better Encoder-only Cross-Encoders: A Controlled Study of Training Strategies for Neural Re-ranking

Victor Morand, Mathias Vast, Basile Van Cooten +3

Cross-encoders fine-tuned from Transformer backbones remain the standard for second-stage re-ranking, and recent knowledge-distillation strategies have closed much of the gap with…

cs.IR2026

MICE: Minimal Interaction Cross-Encoders for efficient Re-ranking

Mathias Vast, Victor Morand, Josiane Mothe +1

In Information Retrieval (IR), cross-encoders deliver state-of-the-art ranking effectiveness but have a high inference cost, limiting their use to second-stage re-rankers. Prior wo…

cs.IR2025

Understanding Matching Mechanisms in Cross-Encoders

Mathias Vast, Basile Van Cooten, Laure Soulier +1

Neural IR architectures, particularly cross-encoders, are highly effective models whose internal mechanisms are mostly unknown. Most works trying to explain their behavior focused…

cs.IR2024★ 2 cited

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…

cs.IR2024★ 1 cited

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…