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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 Page: 1 2 3 4 5...7 Hits 1 – 20 of 130 1 WANLI: Worker and AI Collaboration for Natural Language Inference Dataset Creation ... Liu, Alisa; Swayamdipta, Swabha; Smith, Noah A.. - : arXiv, 2022 BASE Show details 2 Annotators with Attitudes: How Annotator Beliefs And Identities Bias Toxic Language Detection ... Sap, Maarten; Swayamdipta, Swabha; Vianna, Laura. - : arXiv, 2021 BASE Show details 3 Probing Across Time: What Does RoBERTa Know and When? ... Liu, Leo Z.; Wang, Yizhong; Kasai, Jungo. - : arXiv, 2021 BASE Show details 4 Specializing Multilingual Language Models: An Empirical Study ... Chau, Ethan C.; Smith, Noah A.. - : arXiv, 2021 BASE Show details 5 Provable Limitations of Acquiring Meaning from Ungrounded Form: What will Future Language Models Understand? ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Goldberg, Yoav; Merrill, William. - : Underline Science Inc., 2021 BASE Show details 6 Measuring Association Between Labels and Free-Text Rationales ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Marasovic, Ana; Smith, Noah A.. - : Underline Science Inc., 2021 BASE Show details 7 Promoting Graph Awareness in Linearized Graph-to-Text Generation ... 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; Hoyle, Alexander; Marasovic, Ana. - : Underline Science Inc., 2021 BASE Show details 8 Challenges in Automated Debiasing for Toxic Language Detection ... Zhou, Xuhui; Sap, Maarten; Swayamdipta, Swabha. - : arXiv, 2021 BASE Show details 9 NeuroLogic A*esque Decoding: Constrained Text Generation with Lookahead Heuristics ... Lu, Ximing; Welleck, Sean; West, Peter. - : arXiv, 2021 BASE Show details 10 Effects of Parameter Norm Growth During Transformer Training: Inductive Bias from Gradient Descent ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Goldberg, Yoav; Merrill, William. - : Underline Science Inc., 2021 BASE Show details 11 Competency Problems: On Finding and Removing Artifacts in Language Data ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Dodge, Jesse; Gardner, Matt. - : Underline Science Inc., 2021 BASE Show details 12 Extracting and Inferring Personal Attributes from Dialogue Wang, Zhilin. - 2021 BASE Show details 13 Positive AI with Social Commonsense Models Sap, Maarten. - 2021 Abstract: Thesis (Ph.D.)--University of Washington, 2021 ; To effectively understand language and safely communicate with humans, machines must not only grasp the surface meanings of texts, but also their underlying social meaning. This requires understanding interpersonal social commonsense, such as knowing to thank someone for giving you a present, as well as accounting for harmful social biases and stereotypes. While understanding these implied social dynamics is easy for most humans, it remains an elusive goal for AI and NLP systems. Importantly, systems that fail to account for these social and power dynamics risk producing redundant, rude, or even harmful outputs. In this dissertation, we take several steps towards making NLP systems more human-centric, socially aware, and equity driven, motivated by the increased prowess and prevalence of AI and NLP technology. In the first part, we investigate methods for enabling NLP systems to reason about and revise the commonsense implications of text. We introduce ATOMIC, the first largescale social commonsense knowledge graph for machines to reason about the causes and effects of everyday situations, and POWERTRANSFORMER, a system to revise the social implications of text using connotation frames of power and agency. In the second part, we tackle the problem of detecting and representing social biases and toxicity in language with socially aware NLP models. We examine shortcomings of existing toxic language detection tools, uncovering strong racial biases which causes text written by African American authors to be flagged as toxic more often than by white authors. Then, we introduce SOCIAL BIAS FRAMES, a new structured linguistic representation for distilling the harmful or biased implications of text in free-text explanations. We conclude by the discussing the contributions of this dissertation as well as future directions towards improving the social awareness and equity of NLP systems. Keyword: Artificial intelligence; Commonsense reasoning; Computer science; Computer science and engineering; language connotations; Linguistics; social biases; toxic language URL: http://hdl.handle.net/1773/47999 BASE Hide details 14 Semantic Comparisons for Natural Language Processing Applications Lin, Lucy. - 2021 BASE Show details 15 Challenges in Automated Debiasing for Toxic Language Detection ZHOU, XUHUI. - 2021 BASE Show details 16 Parsing with Multilingual BERT, a Small Corpus, and a Small Treebank ... Chau, Ethan C.; Lin, Lucy H.; Smith, Noah A.. - : arXiv, 2020 BASE Show details 17 The Multilingual Amazon Reviews Corpus ... Keung, Phillip; Lu, Yichao; Szarvas, György. - : arXiv, 2020 BASE Show details 18 Unsupervised Bitext Mining and Translation via Self-trained Contextual Embeddings ... Keung, Phillip; Salazar, Julian; Lu, Yichao. - : arXiv, 2020 BASE Show details 19 Evaluating Models' Local Decision Boundaries via Contrast Sets ... Gardner, Matt; Artzi, Yoav; Basmova, Victoria. - : arXiv, 2020 BASE Show details 20 Grounded Compositional Outputs for Adaptive Language Modeling ... Pappas, Nikolaos; Mulcaire, Phoebe; Smith, Noah A.. - : arXiv, 2020 BASE Show details Page: 1 2 3 4 5...7

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