Agarwal, Rishabh

Gemma 3 Technical Report

Gemma Team, Kamath, A., Ferret, J., Pathak, S., Vieillard, N., Merhej, R., Perrin, S., Matejovicova, T., Ramé, A., Rivière, M., et al. (2025) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 1,156

Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Gemini Team, Georgiev, P., Lei, V. I., Burnell, R., Bai, L., Gulati, A., Tanzer, G., Vincent, D., Pan, Z., Wang, S., et al. (2024) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 306

Gemma 2: Improving Open Language Models at a Practical Size

Gemma Team, Riviere, M., Pathak, S., Sessa, P. G., Hardin, C., Bhupatiraju, S., Hussenot, L., Mesnard, T., Shahriari, B., Ramé, A., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 149

Deep Reinforcement Learning at the Edge of the Statistical Precipice

Agarwal, R., Schwarzer, M., Castro, P. S., Courville, A., & Bellemare, M. G. (2021) · arXiv

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 142

Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Comanici, G., Bieber, E., Schaekermann, M., Pasupat, I., Sachdeva, N., Dhillon, I., Blistein, M., Ram, O., Zhang, D., Rosen, E., et al. (2025) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 69

On scalable oversight with weak LLMs judging strong LLMs

Kenton, Z., Siegel, N. Y., Kramár, J., Brown-Cohen, J., Albanie, S., Bulian, J., Agarwal, R., Lindner, D., Tang, Y., Goodman, N. D., et al. (2024) · arXiv

Ethics and Social Impacts of AITopic Modeling

Cited by 66

Waymax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Research

Gulino, C., Fu, J., Luo, W., Tucker, G., Bronstein, E., Lu, Y., Harb, J., Pan, X., Wang, Y., Chen, X., et al. (2023) · arXiv

Autonomous Vehicle Technology and SafetyTraffic control and management

Cited by 48

RL Unplugged: A Suite of Benchmarks for Offline Reinforcement Learning

Gulcehre, C., Wang, Z., Novikov, A., Paine, T. L., Colmenarejo, S. G., Zolna, K., Agarwal, R., Merel, J., Mankowitz, D., Paduraru, C., et al. (2020) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 42

Many-Shot In-Context Learning

Agarwal, R., Singh, A., Zhang, L. M., Bohnet, B., Rosias, L., Chan, S., Zhang, B., Anand, A., Abbas, Z., Nova, A., et al. (2024) · arXiv

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 35

Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models

Singh, A., Co-Reyes, J. D., Agarwal, R., Anand, A., Patil, P., Garcia, X., Liu, P. J., Harrison, J., Lee, J., Xu, K., et al. (2023) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 10

Bigger, Better, Faster: Human-level Atari with human-level efficiency

Schwarzer, M., Obando-Ceron, J., Courville, A., Bellemare, M., Agarwal, R., & Castro, P. S. (2023) · arXiv

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 9

Training Language Models to Self-Correct via Reinforcement Learning

Kumar, A., Zhuang, V., Agarwal, R., Su, Y., Co-Reyes, J. D., Singh, A., Baumli, K., Iqbal, S., Bishop, C., Roelofs, R., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 9

DistillSpec: Improving Speculative Decoding via Knowledge Distillation

Zhou, Y., Lyu, K., Rawat, A. S., Menon, A. K., Rostamizadeh, A., Kumar, S., Kagy, J.-F., & Agarwal, R. (2023) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 9

The Dormant Neuron Phenomenon in Deep Reinforcement Learning

Sokar, G., Agarwal, R., Castro, P. S., & Evci, U. (2023) · arXiv

Reinforcement Learning in RoboticsNeural Networks and Applications

Cited by 8

Offline Q-Learning on Diverse Multi-Task Data Both Scales And Generalizes

Kumar, A., Agarwal, R., Geng, X., Tucker, G., & Levine, S. (2022) · arXiv

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 4

Not All LLM Reasoners Are Created Equal

Hosseini, A., Sordoni, A., Toyama, D., Courville, A., & Agarwal, R. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 3

V-STaR: Training Verifiers for Self-Taught Reasoners

Hosseini, A., Yuan, X., Malkin, N., Courville, A., Sordoni, A., & Agarwal, R. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 3