Few-shot In-Context Preference Learning Using Large Language Models: Environment Details | HackerNoonThe article provides a detailed framework for evaluating tasks in IsaacGym, highlighting key observation and action dimensions across nine tasks.
Detailed Results of the Foundation Benchmark | HackerNoonMost model performance metrics are close to random baselines, indicating a lack of discernible proficiency in key tasks.