Papers with lilGym

1 papers
lilGym: Natural Language Visual Reasoning with Reinforcement Learning (2023.acl-long)

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Challenge: Existing approaches to language-conditioned reinforcement learning in visual environments are limited by language semantics.
Approach: They propose a new benchmark for language-conditioned reinforcement learning in visual environments . they annotate 2,661 highly-compositional human-written natural language statements .
Outcome: The proposed approach is based on 2,661 highly-compositional human-written natural language statements grounded in an interactive visual environment.

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