Piche, Alexandre

18 publications

NeurIPS 2025 How to Train Your LLM Web Agent: A Statistical Diagnosis Dheeraj Vattikonda, Santhoshi Ravichandran, Emiliano Penaloza, Hadi Nekoei, Thibault Le Sellier de Chezelles, Megh Thakkar, Nicolas Gontier, Miguel Muñoz-Mármol, Sahar Omidi Shayegan, Stefania Raimondo, Xue Liu, Alexandre Drouin, Alexandre Piché, Alexandre Lacoste, Massimo Caccia

TMLR 2025 LLMs Can Learn Self-Restraint Through Iterative Self-Reflection Alexandre Piché, Aristides Milios, Dzmitry Bahdanau, Christopher Pal

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

TMLR 2024 Exploring Validation Metrics for Offline Model-Based Optimisation with Diffusion Models Christopher Beckham, Alexandre Piché, David Vazquez, Christopher Pal

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

ICLRW 2024 Self-Evaluation and Self-Prompting to Improve the Reliability of LLMs Alexandre Piché, Aristides Milios, Dzmitry Bahdanau, Christopher Pal

TMLR 2023 Bridging the Gap Between Target Networks and Functional Regularization Alexandre Piché, Valentin Thomas, Joseph Marino, Rafael Pardinas, Gian Maria Marconi, Christopher Pal, Mohammad Emtiyaz Khan

ICMLW 2023 Causal Discovery with Language Models as Imperfect Experts Stephanie Long, Alexandre Piché, Valentina Zantedeschi, Tibor Schuster, Alexandre Drouin

ICML 2023 Mastering the Unsupervised Reinforcement Learning Benchmark from Pixels Sai Rajeswar, Pietro Mazzaglia, Tim Verbelen, Alexandre Piché, Bart Dhoedt, Aaron Courville, Alexandre Lacoste

ICLRW 2022 A Probabilistic Perspective on Reinforcement Learning via Supervised Learning Alexandre Piché, Rafael Pardinas, David Vazquez, Christopher Pal

NeurIPSW 2022 Can Large Language Models Build Causal Graphs? Stephanie Long, Tibor Schuster, Alexandre Piché

NeurIPSW 2022 Implicit Offline Reinforcement Learning via Supervised Learning Alexandre Piché, Rafael Pardinas, David Vazquez, Igor Mordatch, Igor Mordatch, Christopher Pal

ICMLW 2022 Unsupervised Model-Based Pre-Training for Data-Efficient Reinforcement Learning from Pixels Sai Rajeswar, Pietro Mazzaglia, Tim Verbelen, Alexandre Piché, Bart Dhoedt, Aaron Courville, Alexandre Lacoste

NeurIPSW 2021 Beyond Target Networks: Improving Deep $q$-Learning with Functional Regularization Alexandre Piché, Joseph Marino, Gian Maria Marconi, Valentin Thomas, Christopher Pal, Mohammad Emtiyaz Khan

NeurIPS 2021 Iterative Amortized Policy Optimization Joseph Marino, Alexandre Piche, Alessandro Davide Ialongo, Yisong Yue

ICLR 2019 Probabilistic Planning with Sequential Monte Carlo Methods Alexandre Piche, Valentin Thomas, Cyril Ibrahim, Yoshua Bengio, Chris Pal

UAI 2018 Adaptive Stochastic Dual Coordinate Ascent for Conditional Random Fields Rémi Le Priol, Alexandre Piché, Simon Lacoste-Julien

CoRL 2018 Reward Estimation for Variance Reduction in Deep Reinforcement Learning Joshua Romoff, Peter Henderson, Alexandre Piché, Vincent François-Lavet, Joelle Pineau