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Hugo Laurençon

4 accepted papers

2026

Gaia2: Benchmarking LLM Agents on Dynamic and Asynchronous Environments

Romain Froger, Amine Benhalloum, Andrey Rusakov, Dheeraj Mekala, Emilien Garreau, Gerard Moreno-Torres Bertran +18
ICLR 2026oral

We introduce **Gaia2**, a benchmark for evaluating large language model agents in realistic, asynchronous environments. Unlike prior static or synchronous evaluations, Gaia2 introduces scenarios where environments evolve independently of agent actions, requiring agents to operate under temporal cons…

Cited by 0Source ↗Scholar ↗
2024

What matters when building vision-language models?

Hugo Laurençon, Leo Tronchon, Matthieu Cord, Victor Sanh
NeurIPS 2024poster

The growing interest in vision-language models (VLMs) has been driven by improvements in large language models and vision transformers. Despite the abundance of literature on this subject, we observe that critical decisions regarding the design of VLMs are often not justified. We argue that these un…

Cited by 213Source ↗PDF ↗Scholar ↗
2023

OBELICS: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents

Hugo Laurençon, Lucile Saulnier, Leo Tronchon, Stas Bekman, Amanpreet Singh, Anton Lozhkov +6
NeurIPS 2023poster

Large multimodal models trained on natural documents, which interleave images and text, outperform models trained on image-text pairs on various multimodal benchmarks. However, the datasets used to train these models have not been released, and the collection process has not been fully specified. W…

Cited by 295Source ↗PDF ↗code ↗Scholar ↗
2022

The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual Dataset

Hugo Laurençon, Lucile Saulnier, Thomas Wang, Christopher Akiki, Albert Villanova del Moral, Teven Le Scao +48
NeurIPS 2022accept

As language models grow ever larger, the need for large-scale high-quality text datasets has never been more pressing, especially in multilingual settings. The BigScience workshop, a 1-year international and multidisciplinary initiative, was formed with the goal of researching and training large lan…

Cited by 214Source ↗PDF ↗Scholar ↗