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20242026
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cs.IR2026

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

Mathias Vast, Victor Morand, Basile van Cooten +3

Cross-encoders deliver state-of-the-art ranking effectiveness in information retrieval, but have a high inference cost. This prevents them from being used as first-stage rankers, b…

cs.IR2026

Reproducing and Comparing Distillation Techniques for Cross-Encoders

Victor Morand, Mathias Vast, Basile Van Cooten +3

Recent advances in Information Retrieval have established transformer-based cross-encoders as a keystone in IR. Recent studies have focused on knowledge distillation and showed tha…

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

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

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…