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AbstractWhile models for Visual Question Answering (VQA) have steadily improved over the years, interacting with one quickly reveals that these models lack consistency. For instance, if a model answers “red” …...

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A Fine-grained Interpretability Evaluation Benchmark for Neural NLP

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AbstractWhile there is increasing concern about the interpretability of neural models, the evaluation of interpretability remains an open problem, due to the lack of proper evaluation datasets and metrics. In …...

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