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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 – 5 of 5 1 Improving Span Representation for Domain-adapted Coreference Resolution ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Field, Anjalie; Gandhi, Nupoor. - : Underline Science Inc., 2021 BASE Show details 2 Influence Tuning: Demoting Spurious Correlations via Instance Attribution and Instance-Driven Updates ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Han, Xiaochuang; Tsvetkov, Yulia. - : Underline Science Inc., 2021 Abstract: Among the most critical limitations of deep learning NLP models are their lack of interpretability, and their reliance on spurious correlations. Prior work proposed various approaches to interpreting the black-box models to unveil the spurious correlations, but the research was primarily used in human-computer interaction scenarios. It still remains underexplored whether or how such model interpretations can be used to automatically "unlearn" confounding features. In this work, we propose influence tuning—a procedure that leverages model interpretations to update the model parameters towards a plausible interpretation (rather than an interpretation that relies on spurious patterns in the data) in addition to learning to predict the task labels. We show that in a controlled setup, influence tuning can help deconfounding the model from spurious patterns in data, significantly outperforming baseline methods that use adversarial training. ... Keyword: Computational Linguistics; Machine Learning; Machine Learning and Data Mining; Natural Language Processing; Neural Network URL: https://underline.io/lecture/39949-influence-tuning-demoting-spurious-correlations-via-instance-attribution-and-instance-driven-updates https://dx.doi.org/10.48448/ecw1-kj20 BASE Hide details 3 SelfExplain: A Self-Explaining Architecture for Neural Text Classifiers ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Balachandran, Vidhisha; Hovy, Eduard. - : Underline Science Inc., 2021 BASE Show details 4 Efficient Test Time Adapter Ensembling for Low-resource Language Varieties ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Sebastian; Neubig, Graham. - : Underline Science Inc., 2021 BASE Show details 5 Evaluating the Morphosyntactic Well-formedness of Generated Texts ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Anastasopoulos, Antonios; Chaudhary, Aditi. - : Underline Science Inc., 2021 BASE Show details

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