2 citations · 3 across the 4 of their papers we have counts for
5 papers · 1 filter
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…
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…
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…
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…