Papers with NLP classification benchmarks

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Contrastive Explanations for Model Interpretability (2021.emnlp-main)

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Challenge: Existing methods for producing model explanations seek all causal factors at once, making them difficult to comprehend.
Approach: They propose a method to produce contrastive explanations in the latent space . they use attribution and token/span attribution to produce models that consider only contrastive reasoning .
Outcome: The proposed method allows model behavior to consider only contrastive reasoning . it also uncovers which aspects of the input are useful for and against particular decisions .

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