Lee, Kimin

Reinforcement Learning with Augmented Data

Laskin, M., Lee, K., Stooke, A., Pinto, L., Abbeel, P., & Srinivas, A. (2020) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 299

Decoupling Representation Learning from Reinforcement Learning

Stooke, A., Lee, K., Abbeel, P., & Laskin, M. (2020) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 123

Trajectory-wise Multiple Choice Learning for Dynamics Generalization in Reinforcement Learning

Seo, Y., Lee, K., Clavera, I., Kurutach, T., Shin, J., & Abbeel, P. (2020) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 20

A Definition of AGI

Hendrycks, D., Song, D., Szegedy, C., Lee, H., Gal, Y., Brynjolfsson, E., Li, S., Zou, A., Levine, L., Han, B., et al. (2025) · arXiv

Psychiatry, Mental Health, NeuroscienceArtificial Intelligence Applications

Cited by 3

Revisiting Multi-Agent Debate as Test-Time Scaling: A Systematic Study of Conditional Effectiveness

Yang, Y., Yi, E., Ko, J., Lee, K., Jin, Z., & Yun, S.-Y. (2025) · arXiv

Multi-Agent Systems and NegotiationAdversarial Robustness in Machine Learning

Cited by 0

Unintended Misalignment from Agentic Fine-Tuning: Risks and Mitigation

Hahm, D., Min, T., Jin, W., & Lee, K. (2025) · arXiv

Adversarial Robustness in Machine LearningEthics and Social Impacts of AI

Cited by 0