Gasse, Maxime

18 publications

TMLR 2025 The BrowserGym Ecosystem for Web Agent Research Thibault Le Sellier de Chezelles, Maxime Gasse, Alexandre Lacoste, Massimo Caccia, Alexandre Drouin, Léo Boisvert, Megh Thakkar, Tom Marty, Rim Assouel, Sahar Omidi Shayegan, Lawrence Keunho Jang, Xing Han Lù, Ori Yoran, Dehan Kong, Frank F. Xu, Siva Reddy, Graham Neubig, Quentin Cappart, Russ Salakhutdinov, Nicolas Chapados

NeurIPSW 2024 AgentMerge: Enhancing Generalization in Fine-Tuned LLM Agents Megh Thakkar, Léo Boisvert, Thibault Le Sellier de Chezelles, Alexandre Piché, Maxime Gasse, Alexandre Lacoste, Massimo Caccia

NeurIPSW 2024 Fine-Tuning Web Agents: It Works, but It's Trickier than You Think Massimo Caccia, Megh Thakkar, Léo Boisvert, Thibault Le Sellier de Chezelles, Alexandre Piché, Nicolas Chapados, Alexandre Drouin, Maxime Gasse, Alexandre Lacoste

NeurIPS 2024 WorkArena++: Towards Compositional Planning and Reasoning-Based Common Knowledge Work Tasks Léo Boisvert, Megh Thakkar, Maxime Gasse, Massimo Caccia, Thibault Le Sellier De Chezelles, Quentin Cappart, Nicolas Chapados, Alexandre Lacoste, Alexandre Drouin

ICML 2024 WorkArena: How Capable Are Web Agents at Solving Common Knowledge Work Tasks? Alexandre Drouin, Maxime Gasse, Massimo Caccia, Issam H. Laradji, Manuel Del Verme, Tom Marty, David Vazquez, Nicolas Chapados, Alexandre Lacoste

ICLRW 2024 WorkArena: How Capable Are Web Agents at Solving Common Knowledge Work Tasks? Alexandre Drouin, Maxime Gasse, Massimo Caccia, Issam H. Laradji, Manuel Del Verme, Tom Marty, Léo Boisvert, Megh Thakkar, Quentin Cappart, David Vazquez, Nicolas Chapados, Alexandre Lacoste

NeurIPSW 2023 The Unsolved Challenges of LLMs as Generalist Web Agents: A Case Study Rim Assouel, Tom Marty, Massimo Caccia, Issam H. Laradji, Alexandre Drouin, Sai Rajeswar, Hector Palacios, Quentin Cappart, David Vazquez, Nicolas Chapados, Maxime Gasse, Alexandre Lacoste

TMLR 2023 Using Confounded Data in Latent Model-Based Reinforcement Learning Maxime Gasse, Damien Grasset, Guillaume Gaudron, Pierre-Yves Oudeyer

NeurIPS 2022 Learning to Branch with Tree MDPs Lara Scavuzzo, Feng Chen, Didier Chetelat, Maxime Gasse, Andrea Lodi, Neil Yorke-Smith, Karen Aardal

TMLR 2022 Lookback for Learning to Branch Prateek Gupta, Elias Boutros Khalil, Didier Chételat, Maxime Gasse, Andrea Lodi, Yoshua Bengio, M. Pawan Kumar

NeurIPSW 2022 Using Confounded Data in Offline RL Maxime Gasse, Damien Grasset, Guillaume Gaudron, Pierre-Yves Oudeyer

NeurIPSW 2020 Ecole: A Gym-like Library for Machine Learning in Combinatorial Optimization Solvers Antoine Prouvost, Justin Dumouchelle, Lara Scavuzzo, Maxime Gasse, Didier Chételat, Andrea Lodi

NeurIPS 2020 Hybrid Models for Learning to Branch Prateek Gupta, Maxime Gasse, Elias Khalil, Pawan Mudigonda, Andrea Lodi, Yoshua Bengio

NeurIPS 2019 Exact Combinatorial Optimization with Graph Convolutional Neural Networks Maxime Gasse, Didier Chetelat, Nicola Ferroni, Laurent Charlin, Andrea Lodi

ECML-PKDD 2016 F-Measure Maximization in Multi-Label Classification with Conditionally Independent Label Subsets Maxime Gasse, Alex Aussem

PGM 2016 Identifying the Irreducible Disjoint Factors of a Multivariate Probability Distribution Maxime Gasse, Alex Aussem

ICML 2015 On the Optimality of Multi-Label Classification Under Subset Zero-One Loss for Distributions Satisfying the Composition Property Maxime Gasse, Alexandre Aussem, Haytham Elghazel

ECML-PKDD 2012 An Experimental Comparison of Hybrid Algorithms for Bayesian Network Structure Learning Maxime Gasse, Alex Aussem, Haytham Elghazel