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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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Contrastive Explanations for Model Interpretability ...
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Abstract:
Anthology paper link: https://aclanthology.org/2021.emnlp-main.120/ Abstract: Contrastive explanations clarify why an event occurred in contrast to another. They are more inherently intuitive to humans to both produce and comprehend. We propose a methodology to produce contrastive explanations for classification models by modifying the representation to disregard non-contrastive information, and modifying model behavior to only be based on contrastive reasoning. Our method is based on projecting model representation to a latent space that captures only the features that are useful (to the model) to differentiate two potential decisions. We demonstrate the value of contrastive explanations by analyzing two different scenarios, using both high-level abstract concept attribution and low-level input token/span attribution, on two widely used text classification tasks. Specifically, we produce explanations for answering: for which label, and against which alternative label, is some aspect of the input useful? And ...
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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/z2dq-8918 https://underline.io/lecture/37855-contrastive-explanations-for-model-interpretability
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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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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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