Papers with NLM’s machine rationales

1 papers
ER-Test: Evaluating Explanation Regularization Methods for Language Models (2022.findings-emnlp)

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Challenge: Explanation regularization (ER) aims to improve NLM generalization by pushing the NLM’s machine rationales to align with human rationale.
Approach: They propose a framework for evaluating ER models’ OOD generalization along three dimensions: unseen datasets, contrast set tests, and functional tests.
Outcome: The proposed framework evaluates ER models’ OOD generalization across unseen datasets, contrast set tests, and functional tests.

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