Papers with self-rationalization models

2 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.
Does Self-Rationalization Improve Robustness to Spurious Correlations? (2022.emnlp-main)

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Challenge: Rationalization is fundamental to human reasoning and learning.
Approach: They evaluate robustness to spurious correlations in encoder-decoder and decoder-only models . authors say explanations can come at the cost of robustness .
Outcome: The proposed model outputs are more interpretable and easier to interact with for end-users than nonrationalizing models.

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