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A Multilingual Perspective Towards the Evaluation of Attribution Methods in Natural Language Inference
[article]
2022
arXiv
pre-print
Most evaluations of attribution methods focus on the English language. In this work, we present a multilingual approach for evaluating attribution methods for the Natural Language Inference (NLI) task in terms of plausibility and faithfulness properties. First, we introduce a novel cross-lingual strategy to measure faithfulness based on word alignments, which eliminates the potential downsides of erasure-based evaluations. We then perform a comprehensive evaluation of attribution methods,
arXiv:2204.05428v1
fatcat:xqvmrzzbwrephpg7qnq4y6ggui