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