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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 4 of 4 1 Frustratingly Simple Pretraining Alternatives to Masked Language Modeling ... Yamaguchi, Atsuki; Chrysostomou, George; Margatina, Katerina. - : arXiv, 2021 BASE Show details 2 Improving the Faithfulness of Attention-based Explanations with Task-specific Information for Text Classification ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Aletras, Nikolaos; Chrysostomou, George. - : Underline Science Inc., 2021 Abstract: Read paper: https://www.aclanthology.org/2021.acl-long.40 Abstract: Neural network architectures in natural language processing often use attention mechanisms to produce probability distributions over input token representations. Attention has empirically been demonstrated to improve performance in various tasks, while its weights have been extensively used as explanations for model predictions. Recent studies (Jain and Wallace, 2019; Serrano and Smith, 2019; Wiegreffe and Pinter, 2019) have showed that it cannot generally be considered as a faithful explanation (Jacovi and Goldberg, 2020) across encoders and tasks. In this paper, we seek to improve the faithfulness of attention-based explanations for text classification. We achieve this by proposing a new family of Task-Scaling (TaSc) mechanisms that learn task-specific non-contextualised information to scale the original attention weights. Evaluation tests for explanation faithfulness, show that the three proposed variants of TaSc improve attention-based ... Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics URL: https://underline.io/lecture/25394-improving-the-faithfulness-of-attention-based-explanations-with-task-specific-information-for-text-classification https://dx.doi.org/10.48448/q32p-7d89 BASE Hide details 3 Enjoy the Salience: Towards Better Transformer-based Faithful Explanations with Word Salience ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Aletras, Nikolaos; Chrysostomou, George. - : Underline Science Inc., 2021 BASE Show details 4 Frustratingly Simple Pretraining Alternatives to Masked Language Modeling ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Aletras, Nikolaos; Chrysostomou, George. - : Underline Science Inc., 2021 BASE Show details

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