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BitFit: Simple Parameter-efficient Fine-tuning for Transformer-based Masked Language-models ...
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Including Signed Languages in Natural Language Processing ...
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Including Signed Languages in Natural Language Processing ...
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Provable Limitations of Acquiring Meaning from Ungrounded Form: What will Future Language Models Understand? ...
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Measuring and Improving Consistency in Pretrained Language Models ...
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Aligning Faithful Interpretations with their Social Attribution ...
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Abstract:
We find that the requirement of model interpretations to be faithful is vague and incomplete. With interpretation by textual highlights as a case-study, we present several failure cases. Borrowing concepts from social science, we identify that the problem is a misalignment between the causal chain of decisions (causal attribution) and the attribution of human behavior to the interpretation (social attribution). We re-formulate faithfulness as an accurate attribution of causality to the model, and introduce the concept of aligned faithfulness: faithful causal chains that are aligned with their expected social behavior. The two steps of causal attribution and social attribution together complete the process of explaining behavior. With this formalization, we characterize various failures of misaligned faithful highlight interpretations, and propose an alternative causal chain to remedy the issues. Finally, we implement highlight explanations of the proposed causal format using contrastive explanations. ...
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Keyword:
Computational Linguistics; Machine Learning; Machine Learning and Data Mining; Natural Language Processing
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URL: https://dx.doi.org/10.48448/fgdk-w171 https://underline.io/lecture/38188-aligning-faithful-interpretations-with-their-social-attribution
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Amnesic Probing: Behavioral Explanation With Amnesic Counterfactuals ...
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Effects of Parameter Norm Growth During Transformer Training: Inductive Bias from Gradient Descent ...
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Asking It All: Generating Contextualized Questions for any Semantic Role ...
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Counterfactual Interventions Reveal the Causal Effect of Relative Clause Representations on Agreement Prediction ...
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Counterfactual Interventions Reveal the Causal Effect of Relative Clause Representations on Agreement Prediction ...
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Simple, Interpretable and Stable Method for Detecting Words with Usage Change across Corpora
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In: ACL 2020 - 58th Annual Meeting of the Association for Computational Linguistics ; https://hal.inria.fr/hal-03161637 ; ACL 2020 - 58th Annual Meeting of the Association for Computational Linguistics, Jul 2020, Seattle / Virtual, United States. pp.538-555, ⟨10.18653/v1/2020.acl-main.51⟩ (2020)
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