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20232026
most citedxCOMET: Transparent Machine Translation Evaluation through Fine-grained Error Detection

17 citations · 45 across the 20 of their papers we have counts for

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Showing 2025Show all

7 papers · 1 filter

cs.LG2025

TowerVision: Understanding and Improving Multilinguality in Vision-Language Models

André G. Viveiros, Patrick Fernandes, Saul Santos +7

Despite significant advances in vision-language models (VLMs), most existing work follows an English-centric design process, limiting their effectiveness in multilingual settings.…

cs.IR2025

ModernVBERT: Towards Smaller Visual Document Retrievers

Paul Teiletche, Quentin Macé, Max Conti +4

Retrieving specific information from a large corpus of documents is a prevalent industrial use case of modern AI, notably due to the popularity of Retrieval-Augmented Generation (R…

cs.CL2025

Scale or Reason? A Compute-Equivalent Analysis of Reasoning Distillation

Nicolas Boizard, Hippolyte Gisserot-Boukhlef, Kevin El Haddad +2

Distilling reasoning traces from strong teacher models has become the standard recipe for building capable small language models. Yet reasoning traces are 5-20 longer than…

cs.CL2025

Should We Still Pretrain Encoders with Masked Language Modeling?

Hippolyte Gisserot-Boukhlef, Nicolas Boizard, Manuel Faysse +5

Learning high-quality text representations is fundamental to a wide range of NLP tasks. While encoder pretraining has traditionally relied on Masked Language Modeling (MLM), recent…

cs.CL2025

EuroLLM-9B: Technical Report

Pedro Henrique Martins, João Alves, Patrick Fernandes +14

This report presents EuroLLM-9B, a large language model trained from scratch to support the needs of European citizens by covering all 24 official European Union languages and 11 a…

cs.IR2025

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings

Max Conti, Manuel Faysse, Gautier Viaud +3

A limitation of modern document retrieval embedding methods is that they typically encode passages (chunks) from the same documents independently, often overlooking crucial context…

cs.CL2025

EuroBERT: Scaling Multilingual Encoders for European Languages

Nicolas Boizard, Hippolyte Gisserot-Boukhlef, Duarte M. Alves +16

General-purpose multilingual vector representations, used in retrieval, regression and classification, are traditionally obtained from bidirectional encoder models. Despite their w…