Charlin, Laurent

34 publications

ICML 2025 Addressing Concept Mislabeling in Concept Bottleneck Models Through Preference Optimization Emiliano Penaloza, Tianyue H. Zhang, Laurent Charlin, Mateo Espinosa Zarlenga

NeurIPS 2025 Discovering Data Structures: Nearest Neighbor Search and Beyond Omar Salemohamed, Laurent Charlin, Shivam Garg, Vatsal Sharan, Gregory Valiant

TMLR 2025 LitLLMs, LLMs for Literature Review: Are We There yet? Shubham Agarwal, Gaurav Sahu, Abhay Puri, Issam H. Laradji, Krishnamurthy Dj Dvijotham, Jason Stanley, Laurent Charlin, Christopher Pal

ICLRW 2025 Preference Optimization for Concept Bottleneck Models Emiliano Penaloza, Tianyue H. Zhang, Laurent Charlin, Mateo Espinosa Zarlenga

CoLLAs 2024 Integrating Present and past in Unsupervised Continual Learning Yipeng Zhang, Laurent Charlin, Richard Zemel, Mengye Ren

ICMLW 2024 Learning to Design Data-Structures: A Case Study of Nearest Neighbor Search Omar Salemohamed, Vatsal Sharan, Shivam Garg, Laurent Charlin, Gregory Valiant

ICML 2024 Towards Modular LLMs by Building and Reusing a Library of LoRAs Oleksiy Ostapenko, Zhan Su, Edoardo Ponti, Laurent Charlin, Nicolas Le Roux, Lucas Caccia, Alessandro Sordoni

NeurIPSW 2023 A Case Study of Instruction Tuning with Mixture of Parameter-Efficient Experts Oleksiy Ostapenko, Lucas Caccia, Zhan Su, Nicolas Le Roux, Laurent Charlin, Alessandro Sordoni

CoLLAs 2023 Challenging Common Assumptions About Catastrophic Forgetting and Knowledge Accumulation Timothée Lesort, Oleksiy Ostapenko, Pau Rodríguez, Diganta Misra, Md Rifat Arefin, Laurent Charlin, Irina Rish

NeurIPS 2023 Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network Tristan Deleu, Mizu Nishikawa-Toomey, Jithendaraa Subramanian, Nikolay Malkin, Laurent Charlin, Yoshua Bengio

ICMLW 2023 Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network Tristan Deleu, Mizu Nishikawa-Toomey, Jithendaraa Subramanian, Nikolay Malkin, Laurent Charlin, Yoshua Bengio

CoLLAs 2023 Task-Agnostic Continual Reinforcement Learning: Gaining Insights and Overcoming Challenges Massimo Caccia, Jonas Mueller, Taesup Kim, Laurent Charlin, Rasool Fakoor

ICLRW 2023 Task-Agnostic Continual Reinforcement Learning: Gaining Insights and Overcoming Challenges Massimo Caccia, Jonas Mueller, Taesup Kim, Laurent Charlin, Rasool Fakoor

NeurIPSW 2022 Attention for Compositional Modularity Oleksiy Ostapenko, Pau Rodriguez, Alexandre Lacoste, Laurent Charlin

CoLLAs 2022 Continual Learning with Foundation Models: An Empirical Study of Latent Replay Oleksiy Ostapenko, Timothee Lesort, Pau Rodriguez, Md Rifat Arefin, Arthur Douillard, Irina Rish, Laurent Charlin

ICML 2022 Learning to Cut by Looking Ahead: Cutting Plane Selection via Imitation Learning Max B Paulus, Giulia Zarpellon, Andreas Krause, Laurent Charlin, Chris Maddison

ICCV 2021 Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations Pau Rodríguez, Massimo Caccia, Alexandre Lacoste, Lee Zamparo, Issam Laradji, Laurent Charlin, David Vazquez

NeurIPS 2021 Continual Learning via Local Module Composition Oleksiy Ostapenko, Pau Rodriguez, Massimo Caccia, Laurent Charlin

NeurIPS 2021 Pretraining Representations for Data-Efficient Reinforcement Learning Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Charlin, R Devon Hjelm, Philip Bachman, Aaron C. Courville

ICLR 2020 Language GANs Falling Short Massimo Caccia, Lucas Caccia, William Fedus, Hugo Larochelle, Joelle Pineau, Laurent Charlin

NeurIPS 2020 Online Fast Adaptation and Knowledge Accumulation (OSAKA): A New Approach to Continual Learning Massimo Caccia, Pau Rodriguez, Oleksiy Ostapenko, Fabrice Normandin, Min Lin, Lucas Page-Caccia, Issam Hadj Laradji, Irina Rish, Alexandre Lacoste, David Vázquez, Laurent Charlin

NeurIPS 2020 Synbols: Probing Learning Algorithms with Synthetic Datasets Alexandre Lacoste, Pau Rodríguez López, Frederic Branchaud-Charron, Parmida Atighehchian, Massimo Caccia, Issam Hadj Laradji, Alexandre Drouin, Matthew Craddock, Laurent Charlin, David Vázquez

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

NeurIPS 2019 Online Continual Learning with Maximal Interfered Retrieval Rahaf Aljundi, Eugene Belilovsky, Tinne Tuytelaars, Laurent Charlin, Massimo Caccia, Min Lin, Lucas Page-Caccia

ICML 2018 Focused Hierarchical RNNs for Conditional Sequence Processing Nan Rosemary Ke, Konrad Żołna, Alessandro Sordoni, Zhouhan Lin, Adam Trischler, Yoshua Bengio, Joelle Pineau, Laurent Charlin, Christopher Pal

NeurIPS 2018 Towards Deep Conversational Recommendations Raymond Li, Samira Ebrahimi Kahou, Hannes Schulz, Vincent Michalski, Laurent Charlin, Chris Pal

AAAI 2017 A Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialogues Iulian Vlad Serban, Alessandro Sordoni, Ryan Lowe, Laurent Charlin, Joelle Pineau, Aaron C. Courville, Yoshua Bengio

AISTATS 2015 Deep Exponential Families Rajesh Ranganath, Linpeng Tang, Laurent Charlin, David M. Blei

NeurIPS 2014 Content-Based Recommendations with Poisson Factorization Prem Gopalan, Laurent Charlin, David Blei

ICML 2013 Stochastic K-Neighborhood Selection for Supervised and Unsupervised Learning Daniel Tarlow, Kevin Swersky, Laurent Charlin, Ilya Sutskever, Rich Zemel

ICML 2012 Active Learning for Matching Problems Laurent Charlin, Richard S. Zemel, Craig Boutilier

UAI 2011 A Framework for Optimizing Paper Matching Laurent Charlin, Richard S. Zemel, Craig Boutilier

UAI 2008 Hierarchical POMDP Controller Optimization by Likelihood Maximization Marc Toussaint, Laurent Charlin, Pascal Poupart

NeurIPS 2006 Automated Hierarchy Discovery for Planning in Partially Observable Environments Laurent Charlin, Pascal Poupart, Romy Shioda