| Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context M Reid, N Savinov, D Teplyashin, D Lepikhin, T Lillicrap, J Alayrac, ... arXiv preprint arXiv:2403.05530, *Core Contributor, 2024 | 3331 | 2024 |
| Gemma 2: Improving open language models at a practical size G Team, M Riviere, S Pathak, PG Sessa, C Hardin, S Bhupatiraju, ... arXiv preprint arXiv:2408.00118, 2024 | 1693 | 2024 |
| Gemini 2.5: Pushing the frontier with advanced reasoning, multimodality, long context, and next generation agentic capabilities G Comanici, E Bieber, M Schaekermann, I Pasupat, N Sachdeva, I Dhillon, ... arXiv preprint arXiv:2507.06261, 2025 | 1337 | 2025 |
| Deep Reinforcement Learning at the Edge of the Statistical Precipice R Agarwal, M Schwarzer, PS Castro, A Courville, MG Bellemare Neural Information Processing Systems (NeurIPS), 𝗢𝘂𝘁𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴 𝗣𝗮𝗽𝗲𝗿 𝗔𝘄𝗮𝗿𝗱, 2021 | 1034 | 2021 |
| Gemma 3 Technical Report G Team, A Kamath, J Ferret, S Pathak, N Vieillard, R Merhej, S Perrin, ... arXiv preprint arXiv:2503.19786, *Core Contributor, 2025 | 899 | 2025 |
| An Optimistic Perspective on Offline Reinforcement Learning R Agarwal, D Schuurmans, M Norouzi International Conference on Machine Learning (ICML), 2020 | 866* | 2020 |
| Neural additive models: Interpretable machine learning with neural nets R Agarwal, L Melnick, Frosst, Zhang, Lengerich, R Caruana, GE Hinton Neural Information Processing Systems (NeurIPS), 𝗦𝗽𝗼𝘁𝗹𝗶𝗴𝗵𝘁, 2021 | 745 | 2021 |
| Revisiting Fundamentals of Experience Replay W Fedus*, P Ramachandran*, R Agarwal, Y Bengio, H Larochelle, ... International Conference on Machine Learning (ICML), 2020 | 433 | 2020 |
| Training Language Models to Self-Correct via Reinforcement Learning A Kumar*, V Zhuang*, R Agarwal*, Y Su*, JD Co-Reyes, A Singh, ... International Conference on Learning Representations (ICLR), 𝐎𝐫𝐚𝐥, 2025 | 357* | 2025 |
| Many-shot in-context learning R Agarwal, A Singh, LM Zhang, B Bohnet, S Chan, A Anand, Z Abbas, ... Neural Information Processing Systems (NeurIPS), 𝗦𝗽𝗼𝘁𝗹𝗶𝗴𝗵𝘁, 2024 | 343* | 2024 |
| On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes R Agarwal, N Vieillard, Y Zhou, P Stanczyk, S Ramos, M Geist, O Bachem International Conference on Learning Representations (ICLR), 2024 | 326* | 2024 |
| Generative verifiers: Reward modeling as next-token prediction L Zhang, A Hosseini, H Bansal, M Kazemi, A Kumar, R Agarwal International Conference on Learning Representations (ICLR), 2025 | 322* | 2025 |
| RL Unplugged: A Collection of Benchmarks for Offline Reinforcement Learning C Gulcehre, Z Wang, A Novikov, T Paine, S Gómez, K Zolna, R Agarwal, ... Advances in Neural Information Processing Systems (NeurIPS), 2020 | 257* | 2020 |
| Contrastive Behavioral Similarity Embeddings for Generalization in Reinforcement Learning R Agarwal, MC Machado, PS Castro, MG Bellemare International Conference on Learning Representations (ICLR), 𝗦𝗽𝗼𝘁𝗹𝗶𝗴𝗵𝘁, 2021 | 256 | 2021 |
| Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models A Singh*, JD Co-Reyes*, R Agarwal*, A Anand, P Patil, PJ Liu, J Harrison, ... Transactions on Machine Learning Research (TMLR), 2024 | 224 | 2024 |
| V-star: Training verifiers for self-taught reasoners A Hosseini, X Yuan, N Malkin, A Courville, A Sordoni, R Agarwal Conference on Language Modelling (CoLM), 2024 | 216 | 2024 |
| Waymax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Research C Gulino, J Fu, W Luo, G Tucker, E Bronstein, Y Lu, J Harb, X Pan, ... Neural Information Processing Systems, NeurIPS, 2023 | 200 | 2023 |
| Rewarding progress: Scaling automated process verifiers for llm reasoning A Setlur, C Nagpal, A Fisch, X Geng, J Eisenstein, R Agarwal, A Agarwal, ... International Conference on Learning Representations (ICLR), 𝗦𝗽𝗼𝘁𝗹𝗶𝗴𝗵𝘁, 2025 | 188 | 2025 |
| The Dormant Neuron Phenomenon in Deep Reinforcement Learning G Sokar, R Agarwal, PS Castro, U Evci International Conference on Machine Learning (ICML), 𝐎𝐫𝐚𝐥, 2023 | 169 | 2023 |
| Bigger, Better, Faster: Human-level Atari with human-level efficiency M Schwarzer, JO Ceron, Courville, Bellemare, PS Castro*, R Agarwal* International Conference on Machine Learning (ICML), 2023 | 168 | 2023 |
Aaron CourvilleFull Professor, DIRO, Université de Montréal, Mila, Cifar CAI chairVerified email at umontreal.ca
