WT5?! Training Text-to-Text Models to Explain their Predictions

30 Apr 2020Sharan NarangColin RaffelKatherine LeeAdam RobertsNoah FiedelKarishma Malkan

Neural networks have recently achieved human-level performance on various challenging natural language processing (NLP) tasks, but it is notoriously difficult to understand why a neural network produced a particular prediction. In this paper, we leverage the text-to-text framework proposed by Raffel et al.(2019) to train language models to output a natural text explanation alongside their prediction... (read more)

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