Learning Efficient State Abstractions with Natural Language Guidance

The author presents a method, LGA, that leverages natural language to automatically create state abstractions for efficient policy learning in robotic tasks. By using language supervision and background knowledge from language models, LGA improves generalization and robustness in task performance.