Papers with EVADE

1 papers
EVADE: LLM-Based Explanation Generation and Validation for Error Detection in NLI (2026.findings-acl)

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Challenge: Human label variation (HLV) arises when multiple labels are valid for the same instance.
Approach: They propose a framework for generating and validating explanations to detect errors using large language models (LLMs) EVADE framework provides broader explanation coverage and requires less human intervention .
Outcome: The proposed framework provides broader explanation coverage, requires less human intervention, and delivers better downstream performance in predicting label distributions.

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