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Found 3 papers, 2 papers with code
Grounding Large Language Models in Interactive Environments with Online Reinforcement Learning
Using an interactive textual environment designed to study higher-level forms of functional grounding, and a set of spatial and navigation tasks, we study several scientific questions: 1) Can LLMs boost sample efficiency for online learning of various RL tasks?
EAGER: Asking and Answering Questions for Automatic Reward Shaping in Language-guided RL
Reinforcement learning (RL) in long horizon and sparse reward tasks is notoriously difficult and requires a lot of training steps.
VisualHints: A Visual-Lingual Environment for Multimodal Reinforcement Learning
The goal is to force an RL agent to use both text and visual features to predict natural language action commands for solving the final task of cooking a meal.
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