25 citations · 133 across the 34 of their papers we have counts for
7 papers · 1 filter
Match Your Words! A Study of Lexical Matching in Neural Information Retrieval
Thibault Formal, Benjamin Piwowarski, Stéphane Clinchant
Neural Information Retrieval models hold the promise to replace lexical matching models, e.g. BM25, in modern search engines. While their capabilities have fully shone on in-domain…
SPLADE v2: Sparse Lexical and Expansion Model for Information Retrieval
Thibault Formal, Carlos Lassance, Benjamin Piwowarski +1
In neural Information Retrieval (IR), ongoing research is directed towards improving the first retriever in ranking pipelines. Learning dense embeddings to conduct retrieval using…
Skim-Attention: Learning to Focus via Document Layout
Laura Nguyen, Thomas Scialom, Jacopo Staiano +1
Transformer-based pre-training techniques of text and layout have proven effective in a number of document understanding tasks. Despite this success, multimodal pre-training models…
SPLADE: Sparse Lexical and Expansion Model for First Stage Ranking
Thibault Formal, Benjamin Piwowarski, Stéphane Clinchant
In neural Information Retrieval, ongoing research is directed towards improving the first retriever in ranking pipelines. Learning dense embeddings to conduct retrieval using effic…
To Beam Or Not To Beam: That is a Question of Cooperation for Language GANs
Thomas Scialom, Paul-Alexis Dray, Sylvain Lamprier +2
Due to the discrete nature of words, language GANs require to be optimized from rewards provided by discriminator networks, via reinforcement learning methods. This is a much harde…
QuestEval: Summarization Asks for Fact-based Evaluation
Thomas Scialom, Paul-Alexis Dray, Patrick Gallinari +4
Summarization evaluation remains an open research problem: current metrics such as ROUGE are known to be limited and to correlate poorly with human judgments. To alleviate this iss…