Maxime Heuillet

According to our database, Maxime Heuillet authored at least 7 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Robust Fine-Tuning from Non-Robust Pretrained Models: Mitigating Suboptimal Transfer With Adversarial Scheduling.

Jonas Ngnawé, Maxime Heuillet, Sabyasachi Sahoo, Yann Pequignot, Ola Ahmad, Audrey Durand, Frédéric Precioso, Christian Gagné

CoRR, September, 2025

A Guide to Robust Generalization: The Impact of Architecture, Pre-training, and Optimization Strategy.

Maxime Heuillet, Rishika Bhagwatkar, Jonas Ngnawé, Yann Pequignot, Alexandre Larouche, Christian Gagné, Irina Rish, Ola Ahmad, Audrey Durand

CoRR, August, 2025

Nested-ReFT: Efficient Reinforcement Learning for Large Language Model Fine-Tuning via Off-Policy Rollouts.

Maxime Heuillet, Yufei Cui, Boxing Chen, Audrey Durand, Prasanna Parthasarathi

CoRR, August, 2025

2024

Neural Active Learning Meets the Partial Monitoring Framework.

Maxime Heuillet, Ola Ahmad, Audrey Durand

Proceedings of the Uncertainty in Artificial Intelligence, 2024

Randomized Confidence Bounds for Stochastic Partial Monitoring.

Maxime Heuillet, Ola Ahmad, Audrey Durand

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2022

A Game-Theoretic Perspective on Risk-Sensitive Reinforcement Learning.

Mathieu Godbout, Maxime Heuillet, Sharath Chandra Raparthy, Rupali Bhati, Audrey Durand

Proceedings of the Workshop on Artificial Intelligence Safety 2022 (SafeAI 2022) co-located with the Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI2022), 2022

2021

CARL: Conditional-value-at-risk Adversarial Reinforcement Learning.

Mathieu Godbout, Maxime Heuillet, Sharath Chandra, Rupali Bhati, Audrey Durand

CoRR, 2021