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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