Papers with LoRA-finetuned vision-language model
ADAPT: Benchmarking Commonsense Planning under Unspecified Affordance Constraints (2026.acl-long)
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| Challenge: | Existing methods for embodied agents focus on directly executing instructions without considering whether objects can be manipulated. |
| Approach: | They propose a benchmark that evaluates embodied agents in dynamic environments . they use plug-and-play module that augments existing planners with explicit affordance reasoning . |
| Outcome: | The proposed benchmark evaluates embodied agents in dynamic environments with unpredictable affordances . ADAPT significantly improves robustness and task success across seen and unseen environments . |