Papers with ADAPT

2 papers
Enabling Discriminative Reasoning in LLMs for Legal Judgment Prediction (2024.findings-emnlp)

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Challenge: Existing large language models (LLMs) underperform in legal judgment prediction due to challenges in understanding case facts and distinguishing between similar charges.
Approach: They propose a framework that allows LLMs to discriminate among charges and a judicial reasoning framework to improve their models for effective legal judgment prediction.
Outcome: The proposed framework improves accuracy and efficiency when dealing with complex and confusing charges.
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 .

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