2 citations · 2 across the 4 of their papers we have counts for
6 papers
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…
MemoReason: Evaluating the Effect of Parametric Memory on Contextual Reasoning in LLMs
Zineddine Tighidet, Andrea Mogini, Jiali Mei +2
Large Language Models (LLMs) perform well on reasoning benchmarks, but it remains unclear whether this reflects genuine contextual reasoning or reliance on facts memorized in their…
QueStER: Query Specification for Generative keyword-based Retrieval
Arthur Satouf, Yuxuan Zong, Habiboulaye Amadou-Boubacar +2
Generative retrieval (GR) differs from the traditional index-then-retrieve pipeline by storing relevance in model parameters and generating retrieval cues directly from the query,…
Context Copying Modulation: The Role of Entropy Neurons in Managing Parametric and Contextual Knowledge Conflicts
Zineddine Tighidet, Andrea Mogini, Hedi Ben-younes +3
The behavior of Large Language Models (LLMs) when facing contextual information that conflicts with their internal parametric knowledge is inconsistent, with no generally accepted…
Rational Retrieval Acts: Leveraging Pragmatic Reasoning to Improve Sparse Retrieval
Arthur Satouf, Gabriel Ben Zenou, Benjamin Piwowarski +2
Current sparse neural information retrieval (IR) methods, and to a lesser extent more traditional models such as BM25, do not take into account the document collection and the comp…
Towards Lossless Token Pruning in Late-Interaction Retrieval Models
Yuxuan Zong, Benjamin Piwowarski
Late interaction neural IR models like ColBERT offer a competitive effectiveness-efficiency trade-off across many benchmarks. However, they require a huge memory space to store the…