72 citations · 87 across the 12 of their papers we have counts for
12 papers
Benchmarking Middle-Trained Language Models for Neural Search
Hervé Déjean, Stéphane Clinchant, Carlos Lassance +2
Middle training methods aim to bridge the gap between the Masked Language Model (MLM) pre-training and the final finetuning for retrieval. Recent models such as CoCondenser, RetroM…
The tale of two MS MARCO -- and their unfair comparisons
Carlos Lassance, Stéphane Clinchant
The MS MARCO-passage dataset has been the main large-scale dataset open to the IR community and it has fostered successfully the development of novel neural retrieval models over t…
A Static Pruning Study on Sparse Neural Retrievers
Carlos Lassance, Simon Lupart, Hervé Dejean +2
Sparse neural retrievers, such as DeepImpact, uniCOIL and SPLADE, have been introduced recently as an efficient and effective way to perform retrieval with inverted indexes. They a…
AToMiC: An Image/Text Retrieval Test Collection to Support Multimedia Content Creation
Jheng-Hong Yang, Carlos Lassance, Rafael Sampaio de Rezende +4
This paper presents the AToMiC (Authoring Tools for Multimedia Content) dataset, designed to advance research in image/text cross-modal retrieval. While vision-language pretrained…
Simple Yet Effective Neural Ranking and Reranking Baselines for Cross-Lingual Information Retrieval
Jimmy Lin, David Alfonso-Hermelo, Vitor Jeronymo +8
The advent of multilingual language models has generated a resurgence of interest in cross-lingual information retrieval (CLIR), which is the task of searching documents in one lan…
Parameter-Efficient Sparse Retrievers and Rerankers using Adapters
Vaishali Pal, Carlos Lassance, Hervé Déjean +1
Parameter-Efficient transfer learning with Adapters have been studied in Natural Language Processing (NLP) as an alternative to full fine-tuning. Adapters are memory-efficient and…