18 citations · 31 across the 6 of their papers we have counts for
6 papers
Gaia2: Benchmarking LLM Agents on Dynamic and Asynchronous Environments
Romain Froger, Pierre Andrews, Matteo Bettini +21
We introduce Gaia2, a benchmark for evaluating large language model agents in realistic, asynchronous environments. Unlike prior static or synchronous evaluations, Gaia2 introduces…
A Cognitive Paradigm Approach to Probe the Perception-Reasoning Interface in VLMs
Mohit Vaishnav, Tanel Tammet
A fundamental challenge in artificial intelligence involves understanding the cognitive mechanisms underlying visual reasoning in sophisticated models like Vision-Language Models (…
Building and better understanding vision-language models: insights and future directions
Hugo Laurençon, Andrés Marafioti, Victor Sanh +1
The field of vision-language models (VLMs), which take images and texts as inputs and output texts, is rapidly evolving and has yet to reach consensus on several key aspects of the…
What matters when building vision-language models?
Hugo Laurençon, Léo Tronchon, Matthieu Cord +1
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…
Unlocking the conversion of Web Screenshots into HTML Code with the WebSight Dataset
Hugo Laurençon, Léo Tronchon, Victor Sanh
Using vision-language models (VLMs) in web development presents a promising strategy to increase efficiency and unblock no-code solutions: by providing a screenshot or a sketch of…
BLESS: Benchmarking Large Language Models on Sentence Simplification
Tannon Kew, Alison Chi, Laura Vásquez-Rodríguez +4
We present BLESS, a comprehensive performance benchmark of the most recent state-of-the-art large language models (LLMs) on the task of text simplification (TS). We examine how wel…