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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 – 6 of 6 1 MM-COVID: A Multilingual and Multimodal Data Repository for Combating COVID-19 Disinformation ... Li, Yichuan; Jiang, Bohan; Shu, Kai. - : Zenodo, 2021 BASE Show details 2 MM-COVID: A Multilingual and Multimodal Data Repository for Combating COVID-19 Disinformation ... Li, Yichuan; Jiang, Bohan; Shu, Kai. - : Zenodo, 2021 BASE Show details 3 Text Adjuncts and Comprehension with University Level Second Language Readers ... Liu, Huan. - : Washington University in St. Louis, 2021 BASE Show details 4 Mitigating Bias in Session-based Cyberbullying Detection: A Non-Compromising Approach ... 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; Cheng, Lu; Hall, Deborah; Liu , Huan; Mosallanezhad, David; Silva, Yasin. - : Underline Science Inc., 2021 Abstract: Read paper: https://www.aclanthology.org/2021.acl-long.168 Abstract: The element of repetition in cyberbullying behavior has directed recent computational studies toward detecting cyberbullying based on a social media session. In contrast to a single text, a session may consist of an initial post and an associated sequence of comments. Yet, emerging efforts to enhance the performance of session-based cyberbullying detection have largely overlooked unintended social biases in existing cyberbullying datasets. For example, a session containing certain demographic-identity terms (e.g., "gay" or "black") is more likely to be classified as an instance of cyberbullying. In this paper, we first show evidence of such bias in models trained on sessions collected from different social media platforms (e.g., Instagram). We then propose a context-aware and model-agnostic debiasing strategy that leverages a reinforcement learning technique, without requiring any extra resources or annotations apart from a pre-defined set ... Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics URL: https://underline.io/lecture/25488-mitigating-bias-in-session-based-cyberbullying-detection-a-non-compromising-approach https://dx.doi.org/10.48448/jcse-7k89 BASE Hide details 5 Learning to Selectively Learn for Weakly-supervised Paraphrase Generation ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Ding , Kaize; Fan, Xing. - : Underline Science Inc., 2021 BASE Show details 6 "Let's Eat Grandma": When Punctuation Matters in Sentence Representation for Sentiment Analysis ... Karami, Mansooreh; Mosallanezhad, Ahmadreza; Mancenido, Michelle V. - : arXiv, 2021 BASE Show details

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