Kumar, Aviral

Gemini: A Family of Highly Capable Multimodal Models

Gemini Team, Anil, R., Borgeaud, S., Alayrac, J.-B., Yu, J., Soricut, R., Schalkwyk, J., Dai, A. M., Hauth, A., Millican, K., et al. (2023) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 990

Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems

Levine, S., Kumar, A., Tucker, G., & Fu, J. (2020) · arXiv

Reinforcement Learning in RoboticsAdvanced Bandit Algorithms Research

Cited by 824

Why Generalization in RL is Difficult: Epistemic POMDPs and Implicit Partial Observability

Ghosh, D., Rahme, J., Kumar, A., Zhang, A., Adams, R. P., & Levine, S. (2021) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 41

Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters

Snell, C., Lee, J., Xu, K., & Kumar, A. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 27

Recursive Introspection: Teaching Language Model Agents How to Self-Improve

Qu, Y., Zhang, T., Garg, N., & Kumar, A. (2024) · Advances in Neural Information Processing Systems 37

AI-based Problem Solving and PlanningIntelligent Tutoring Systems and Adaptive Learning

Cited by 21

DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning

Bai, H., Zhou, Y., Cemri, M., Pan, J., Suhr, A., Levine, S., & Kumar, A. (2024) · arXiv

Reinforcement Learning in RoboticsIoT and Edge/Fog Computing

Cited by 20

DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning

Bai, H., Zhou, Y., Cemri, M., Pan, J., Suhr, A., Levine, S., & Kumar, A. (2024) · Advances in Neural Information Processing Systems 37

Reinforcement Learning in RoboticsIoT and Edge/Fog Computing

Cited by 20

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

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