Papers with explanation metric

1 papers
ZARA: Improving Few-Shot Self-Rationalization for Small Language Models (2023.findings-emnlp)

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Challenge: Recent studies demonstrate great performance gain for self-rationalization by few-shot prompting LMs with rationale-augmented exemplars.
Approach: They propose to leverage explanations for small LMs to improve few-shot self-rationalization by reducing the problem of plausibility judgement to natural language inference.
Outcome: The proposed approach achieves SOTA performance on the FEB benchmark, for both the task accuracy and the explanation metric.

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