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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