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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 – 8 of 8 1 Crossing the Conversational Chasm: A Primer on Natural Language Processing for Multilingual Task-Oriented Dialogue Systems ... Razumovskaia, Evgeniia; Glavaš, Goran; Majewska, Olga. - : arXiv, 2021 BASE Show details 2 On Cross-Lingual Retrieval with Multilingual Text Encoders ... Litschko, Robert; Vulić, Ivan; Ponzetto, Simone Paolo. - : arXiv, 2021 BASE Show details 3 Evaluating Multilingual Text Encoders for Unsupervised Cross-Lingual Retrieval ... Litschko, Robert; Vulić, Ivan; Ponzetto, Simone Paolo. - : arXiv, 2021 BASE Show details 4 RedditBias: A Real-World Resource for Bias Evaluation and Debiasing of Conversational Language Models ... 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; Barikeri, Soumya; Glavaš, Goran; Lauscher, Anne; Vulić, Ivan. - : Underline Science Inc., 2021 Abstract: Read paper: https://www.aclanthology.org/2021.acl-long.151 Abstract: Text representation models are prone to exhibit a range of societal biases, reflecting the non-controlled and biased nature of the underlying pretraining data, which consequently leads to severe ethical issues and even bias amplification. Recent work has predominantly focused on measuring and mitigating bias in pretrained language models. Surprisingly, the landscape of bias measurements and mitigation resources and methods for conversational language models is still very scarce: it is limited to only a few types of bias, artificially constructed resources, and completely ignores the impact that debiasing methods may have on the final perfor mance in dialog tasks, e.g., conversational response generation. In this work, we present REDDITBIAS, the first conversational data set grounded in the actual human conversations from Reddit, allowing for bias measurement and mitigation across four important bias dimensions: gender,race,religion, and ... Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics URL: https://underline.io/lecture/25465-redditbias-a-real-world-resource-for-bias-evaluation-and-debiasing-of-conversational-language-models https://dx.doi.org/10.48448/b20r-x634 BASE Hide details 5 LexFit: Lexical Fine-Tuning of Pretrained Language Models ... 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; Glavaš, Goran; Korhonen, Anna. - : Underline Science Inc., 2021 BASE Show details 6 Verb Knowledge Injection for Multilingual Event Processing ... 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; Glavaš, Goran; Korhonen, Anna. - : Underline Science Inc., 2021 BASE Show details 7 Is supervised syntactic parsing beneficial for language understanding tasks? An empirical investigation Glavaš, Goran; Vulić, Ivan. - : Association for Computational Linguistics, 2021 BASE Show details 8 Evaluating multilingual text encoders for unsupervised cross-lingual retrieval Litschko, Robert; Vulić, Ivan; Ponzetto, Simone Paolo. - : Springer, 2021 BASE Show details

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