Clavera, Ignasi

Learning to Adapt in Dynamic, Real-World Environments through Meta-Reinforcement Learning

Nagabandi, A., Clavera, I., Liu, S., Fearing, R. S., Abbeel, P., Levine, S., & Finn, C. (2018) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 370

Benchmarking Model-Based Reinforcement Learning

Wang, T., Bao, X., Clavera, I., Hoang, J., Wen, Y., Langlois, E., Zhang, S., Zhang, G., Abbeel, P., & Ba, J. (2019) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 226

OpenAI GPT-5 System Card

Singh, A., Fry, A., Perelman, A., Tart, A., Ganesh, A., El-Kishky, A., McLaughlin, A., Low, A., Ostrow, A., Ananthram, A., et al. (2026) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 26

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

Competitive Programming with Large Reasoning Models

OpenAI, :, El-Kishky, A., Wei, A., Saraiva, A., Minaiev, B., Selsam, D., Dohan, D., Song, F., Lightman, H., et al. (2025) · arXiv

Teaching and Learning ProgrammingAI-based Problem Solving and Planning

Cited by 6