Rishabh Agarwal
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
32
Venues
7
Active years
2017–2025
Best venue rank
A*
Where they publish
Papers
32 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICLR | Smaller, Weaker, Yet Better: Training LLM Reasoners via Compute-Optimal Sampling. | Hritik Bansal, Arian Hosseini, Rishabh Agarwal, Vinh Q. Tran, Mehran Kazemi |
| 2025 | ICLR | Inference-Aware Fine-Tuning for Best-of-N Sampling in Large Language Models. | Yinlam Chow, Guy Tennenholtz, Izzeddin Gur, Vincent Zhuang, Bo Dai, Aviral Kumar, Rishabh Agarwal, Sridhar Thiagarajan, Craig Boutilier, Aleksandra Faust |
| 2025 | ICLR | Training Language Models to Self-Correct via Reinforcement Learning. | Aviral Kumar, Vincent Zhuang, Rishabh Agarwal, Yi Su, John D. Co-Reyes, Avi Singh, Kate Baumli, Shariq Iqbal, Colton Bishop, Rebecca Roelofs, Lei M. Zhang, Kay McKinney, Disha Shrivastava, Cosmin Paduraru, George Tucker, Doina Precup, Feryal M. P. Behbahani, Aleksandra Faust |
| 2025 | ICLR | Asynchronous RLHF: Faster and More Efficient Off-Policy RL for Language Models. | Michael Noukhovitch, Shengyi Huang, Sophie Xhonneux, Arian Hosseini, Rishabh Agarwal, Aaron C. Courville |
| 2025 | ICLR | Rewarding Progress: Scaling Automated Process Verifiers for LLM Reasoning. | Amrith Setlur, Chirag Nagpal, Adam Fisch, Xinyang Geng, Jacob Eisenstein, Rishabh Agarwal, Alekh Agarwal, Jonathan Berant, Aviral Kumar |
| 2025 | ICLR | Speculative Knowledge Distillation: Bridging the Teacher-Student Gap Through Interleaved Sampling. | Wenda Xu, Rujun Han, Zifeng Wang, Long T. Le, Dhruv Madeka, Lei Li, William Yang Wang, Rishabh Agarwal, Chen-Yu Lee, Tomas Pfister |
| 2025 | ICLR | Generative Verifiers: Reward Modeling as Next-Token Prediction. | Lunjun Zhang, Arian Hosseini, Hritik Bansal, Mehran Kazemi, Aviral Kumar, Rishabh Agarwal |
| 2025 | ICML | Reward-Guided Prompt Evolving in Reinforcement Learning for LLMs. | Ziyu Ye, Rishabh Agarwal, Tianqi Liu, Rishabh Joshi, Sarmishta Velury, Quoc V. Le, Qijun Tan, Yuan Liu |
| 2024 | ICLR | On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes. | Rishabh Agarwal, Nino Vieillard, Yongchao Zhou, Piotr Stanczyk, Sabela Ramos Garea, Matthieu Geist, Olivier Bachem |
| 2024 | ICLR | DistillSpec: Improving Speculative Decoding via Knowledge Distillation. | Yongchao Zhou, Kaifeng Lyu, Ankit Singh Rawat, Aditya Krishna Menon, Afshin Rostamizadeh, Sanjiv Kumar, Jean-Franois Kagy, Rishabh Agarwal |
| 2024 | ICML | Stop Regressing: Training Value Functions via Classification for Scalable Deep RL. | Jesse Farebrother, Jordi Orbay, Quan Vuong, Adrien Ali Taga, Yevgen Chebotar, Ted Xiao, Alex Irpan, Sergey Levine, Pablo Samuel Castro, Aleksandra Faust, Aviral Kumar, Rishabh Agarwal |
| 2024 | ICML | SiT: Symmetry-invariant Transformers for Generalisation in Reinforcement Learning. | Matthias Weissenbacher, Rishabh Agarwal, Yoshinobu Kawahara |
| 2023 | AISTATS | A Novel Stochastic Gradient Descent Algorithm for Learning Principal Subspaces. | Charline Le Lan, Joshua Greaves, Jesse Farebrother, Mark Rowland, Fabian Pedregosa, Rishabh Agarwal, Marc G. Bellemare |
| 2023 | ICLR | Proto-Value Networks: Scaling Representation Learning with Auxiliary Tasks. | Jesse Farebrother, Joshua Greaves, Rishabh Agarwal, Charline Le Lan, Ross Goroshin, Pablo Samuel Castro, Marc G. Bellemare |
| 2023 | ICLR | Offline Q-learning on Diverse Multi-Task Data Both Scales And Generalizes. | Aviral Kumar, Rishabh Agarwal, Xinyang Geng, George Tucker, Sergey Levine |
| 2023 | ICLR | Revisiting Bisimulation: A Sampling-Based State Similarity Pseudo-metric. | Charline Le Lan, Rishabh Agarwal |
| 2023 | ICLR | Investigating Multi-task Pretraining and Generalization in Reinforcement Learning. | Adrien Ali Taga, Rishabh Agarwal, Jesse Farebrother, Aaron C. Courville, Marc G. Bellemare |
| 2023 | ICML | Bootstrapped Representations in Reinforcement Learning. | Charline Le Lan, Stephen Tu, Mark Rowland, Anna Harutyunyan, Rishabh Agarwal, Marc G. Bellemare, Will Dabney |
| 2023 | ICML | Bigger, Better, Faster: Human-level Atari with human-level efficiency. | Max Schwarzer, Johan S. Obando-Ceron, Aaron C. Courville, Marc G. Bellemare, Rishabh Agarwal, Pablo Samuel Castro |
| 2023 | ICML | The Dormant Neuron Phenomenon in Deep Reinforcement Learning. | Ghada Sokar, Rishabh Agarwal, Pablo Samuel Castro, Utku Evci |
| 2023 | ICML | Revisiting Bellman Errors for Offline Model Selection. | Joshua P. Zitovsky, Daniel de Marchi, Rishabh Agarwal, Michael Rene Kosorok |
| 2022 | AAAI | Control-Oriented Model-Based Reinforcement Learning with Implicit Differentiation. | Evgenii Nikishin, Romina Abachi, Rishabh Agarwal, Pierre-Luc Bacon |
| 2022 | AISTATS | On the Generalization of Representations in Reinforcement Learning. | Charline Le Lan, Stephen Tu, Adam Oberman, Rishabh Agarwal, Marc G. Bellemare |
| 2022 | ICLR | DR3: Value-Based Deep Reinforcement Learning Requires Explicit Regularization. | Aviral Kumar, Rishabh Agarwal, Tengyu Ma, Aaron C. Courville, George Tucker, Sergey Levine |
| 2022 | IGARSS | Detection Of Crop Water Stress In Maize Using Drone Based Hyperspectral Imaging. | Jayantrao Mohite, Suryakant A. Sawant, Rishabh Agarwal, Ankur Pandit, Srinivasu Pappula |
| 2021 | ICLR | Contrastive Behavioral Similarity Embeddings for Generalization in Reinforcement Learning. | Rishabh Agarwal, Marlos C. Machado, Pablo Samuel Castro, Marc G. Bellemare |
| 2021 | ICLR | Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement Learning. | Aviral Kumar, Rishabh Agarwal, Dibya Ghosh, Sergey Levine |
| 2020 | ICML | An Optimistic Perspective on Offline Reinforcement Learning. | Rishabh Agarwal, Dale Schuurmans, Mohammad Norouzi |
| 2020 | ICML | Revisiting Fundamentals of Experience Replay. | William Fedus, Prajit Ramachandran, Rishabh Agarwal, Yoshua Bengio, Hugo Larochelle, Mark Rowland, Will Dabney |
| 2019 | ICML | Learning to Generalize from Sparse and Underspecified Rewards. | Rishabh Agarwal, Chen Liang, Dale Schuurmans, Mohammad Norouzi |
| 2017 | GLOBECOM | S-Pencil: A Smart Pencil Grip Monitoring System for Kids Using Sensors. | Prakhar Gupta, Rishabh Agarwal, Surbhi Saraswat, Hari Prabhat Gupta, Tanima Dutta |
| 2017 | ISDA | Computing Theory Prime Implicates in Modal Logic. | Manoj K. Raut, Tushar V. Kokane, Rishabh Agarwal |