| Human alignment of large language models through online preference optimisation D Calandriello, D Guo, R Munos, M Rowland, Y Tang, BA Pires, ... arXiv preprint arXiv:2403.08635, 2024 | | 2024 |
| Generalized preference optimization: A unified approach to offline alignment Y Tang, ZD Guo, Z Zheng, D Calandriello, R Munos, M Rowland, ... arXiv preprint arXiv:2402.05749, 2024 | 2 | 2024 |
| Decoding-time realignment of language models T Liu, S Guo, L Bianco, D Calandriello, Q Berthet, F Llinares, J Hoffmann, ... arXiv preprint arXiv:2402.02992, 2024 | | 2024 |
| Nash learning from human feedback R Munos, M Valko, D Calandriello, MG Azar, M Rowland, D Guo, Y Tang, ... arXiv preprint arXiv:2312.00886, 2024 | 14 | 2024 |
| Demonstration-regularized RL D Tiapkin, D Belomestny, D Calandriello, E Moulines, A Naumov, ... International Conference on Learning Representations, 2024 | 2* | 2024 |
| A general theoretical paradigm to understand learning from human preferences MG Azar, M Rowland, B Piot, D Guo, D Calandriello, M Valko, R Munos International Conference on Artificial Intelligence and Statistics, 2024 | 53 | 2024 |
| Local and adaptive mirror descents in extensive-form games C Fiegel, P Ménard, T Kozuno, R Munos, V Perchet, M Valko arXiv preprint arXiv:2309.00656, 2024 | 1 | 2024 |
| Unlocking the power of representations in long-term novelty-based exploration A Saade, S Kapturowski, D Calandriello, C Blundell, P Sprechmann, ... International Conference on Learning Representations, 2024 | 4 | 2024 |
| Sharp deviations bounds for Dirichlet weighted sums with application to analysis of Bayesian algorithms D Belomestny, P Menard, A Naumov, D Tiapkin, M Valko arXiv preprint arXiv:2304.03056, 2024 | | 2024 |
| Model-free posterior sampling via learning rate randomization D Tiapkin, D Belomestny, D Calandriello, E Moulines, R Munos, ... Neural Information Processing Systems, 2023 | | 2023 |
| Half-Hop: A graph upsampling approach for slowing down message passing M Azabou, V Ganesh, S Thakoor, CH Lin, L Sathidevi, R Liu, M Valko, ... International Conference on Machine Learning, 2023 | 6 | 2023 |
| Quantile credit assignment T Mesnard, W Chen, A Saade, Y Tang, M Rowland, T Weber, C Lyle, ... International Conference on Machine Learning, 2023 | 2 | 2023 |
| Curiosity in hindsight: Intrinsic exploration in stochastic environments D Jarrett, C Tallec, F Altché, T Mesnard, R Munos, M Valko International Conference on Machine Learning, 2023 | 9 | 2023 |
| Fast rates for maximum entropy exploration D Tiapkin, D Belomestny, D Calandriello, E Moulines, R Munos, ... International Conference on Machine Learning, 2023 | 7 | 2023 |
| Middle-mile logistics through the lens of goal-conditioned reinforcement learning O Eberhard, T Cuvelier, M Valko, B De Backer NeurIPS 2023 Workshop: Goal-conditioned RL, 2023 | | 2023 |
| DoMo-AC: Doubly multi-step off-policy actor-critic algorithm Y Tang, T Kozuno, M Rowland, A Harutyunyan, R Munos, BÁ Pires, ... International Conference on Machine Learning, 2023 | | 2023 |
| VA-learning as a more efficient alternative to Q-learning Y Tang, R Munos, M Rowland, M Valko International Conference on Machine Learning, 2023 | 2 | 2023 |
| Regularization and variance-weighted regression achieves minimax optimality in linear MDPs: Theory and practice T Kitamura, T Kozuno, Y Tang, N Vieillard, M Valko, W Yang, J Mei, ... International Conference on Machine Learning, 2023 | 2 | 2023 |
| Adapting to game trees in zero-sum imperfect information games C Fiegel, P Ménard, T Kozuno, R Munos, V Perchet, M Valko International Conference on Machine Learning, 2023 | 4 | 2023 |
| Understanding self-predictive learning for reinforcement learning Y Tang, ZD Guo, PH Richemond, BÁ Pires, Y Chandak, R Munos, ... International Conference on Machine Learning, 2023 | 20 | 2023 |
Rémi MunosDeepMindVerified email at inria.fr
