activity
20152024
most citedVerification of railway interlocking systems

28 citations · 51 across the 9 of their papers we have counts for

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Showing cs.LGShow all

5 papers · 1 filter

cs.LG20244 cited

The BrowserGym Ecosystem for Web Agent Research

Thibault Le Sellier De Chezelles, Maxime Gasse, Alexandre Drouin +17

The BrowserGym ecosystem addresses the growing need for efficient evaluation and benchmarking of web agents, particularly those leveraging automation and Large Language Models (LLM…

cs.LG2024

Towards a Generic Representation of Combinatorial Problems for Learning-Based Approaches

Léo Boisvert, Hélène Verhaeghe, Quentin Cappart

In recent years, there has been a growing interest in using learning-based approaches for solving combinatorial problems, either in an end-to-end manner or in conjunction with trad…

cs.LG2024

WorkArena: How Capable Are Web Agents at Solving Common Knowledge Work Tasks?

Alexandre Drouin, Maxime Gasse, Massimo Caccia +9

We study the use of large language model-based agents for interacting with software via web browsers. Unlike prior work, we focus on measuring the agents' ability to perform tasks…

cs.LG20227 cited

The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights

Maxime Gasse, Quentin Cappart, Jonas Charfreitag +38

Combinatorial optimization is a well-established area in operations research and computer science. Until recently, its methods have focused on solving problem instances in isolatio…

cs.LG2021

SeaPearl: A Constraint Programming Solver guided by Reinforcement Learning

Félix Chalumeau, Ilan Coulon, Quentin Cappart +1

The design of efficient and generic algorithms for solving combinatorial optimization problems has been an active field of research for many years. Standard exact solving approache…