6 papers
ViDoRe V3: A Comprehensive Evaluation of Retrieval Augmented Generation in Complex Real-World Scenarios
António Loison, Quentin Macé, Antoine Edy +7
Retrieval-Augmented Generation (RAG) pipelines must address challenges beyond simple single-document retrieval, such as interpreting visual elements (tables, charts, images), synth…
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…
Surfer 2: The Next Generation of Cross-Platform Computer Use Agents
Mathieu Andreux, Märt Bakler, Yanael Barbier +50
Building agents that generalize across web, desktop, and mobile environments remains an open challenge, as prior systems rely on environment-specific interfaces that limit cross-pl…
ViDoRe Benchmark V2: Raising the Bar for Visual Retrieval
Quentin Macé, António Loison, Manuel Faysse
The ViDoRe Benchmark V1 was approaching saturation with top models exceeding 90% nDCG@5, limiting its ability to discern improvements. ViDoRe Benchmark V2 introduces realistic, cha…
CroissantLLM: A Truly Bilingual French-English Language Model
Manuel Faysse, Patrick Fernandes, Nuno M. Guerreiro +13
We introduce CroissantLLM, a 1.3B language model pretrained on a set of 3T English and French tokens, to bring to the research and industrial community a high-performance, fully op…
GroUSE: A Benchmark to Evaluate Evaluators in Grounded Question Answering
Sacha Muller, António Loison, Bilel Omrani +1
Retrieval-Augmented Generation (RAG) has emerged as a common paradigm to use Large Language Models (LLMs) alongside private and up-to-date knowledge bases. In this work, we address…