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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 – 12 of 12 1 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. - : Underline Science Inc., 2021 BASE Show details 2 From Zero to Hero: On the Limitations of Zero-Shot Cross-Lingual Transfer with Multilingual Transformers ... Lauscher, Anne; Ravishankar, Vinit; Vulic, Ivan. - : Apollo - University of Cambridge Repository, 2020 BASE Show details 3 From Zero to Hero: On the Limitations of Zero-Shot Cross-Lingual Transfer with Multilingual Transformers ... Lauscher, Anne; Ravishankar, Vinit; Vulić, Ivan. - : arXiv, 2020 BASE Show details 4 Specializing Unsupervised Pretraining Models for Word-Level Semantic Similarity ... The 28th International Conference on Computational Linguistics 2020; Glavaš, Goran; Korhonen, Anna. - : Underline Science Inc., 2020 BASE Show details 5 Specializing Unsupervised Pretraining Models for Word-Level Semantic Similarity ... Lauscher, Anne; Vulic, Ivan; Ponti, Edoardo. - : Apollo - University of Cambridge Repository, 2020 BASE Show details 6 Specializing Unsupervised Pretraining Models for Word-Level Semantic Similarity Lauscher, Anne; Vulic, Ivan; Ponti, Edoardo. - : International Committee on Computational Linguistics, 2020. : https://www.aclweb.org/anthology/2020.coling-main.118, 2020. : Proceedings of the 28th International Conference on Computational Linguistics (COLING 2020), 2020 BASE Show details 7 From Zero to Hero: On the Limitations of Zero-Shot Cross-Lingual Transfer with Multilingual Transformers Ravishankar, Vinit; Glavas, Goran; Lauscher, Anne. - : Association for Computational Linguistics, 2020. : Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP 2020), 2020 BASE Show details 8 Specializing unsupervised pretraining models for word-level semantic similarity Ponti, Edoardo Maria; Korhonen, Anna; Vulić, Ivan. - : Association for Computational Linguistics, ACL, 2020 BASE Show details 9 Common sense or world knowledge? Investigating adapter-based knowledge injection into pretrained transformers Lauscher, Anne; Majewska, Olga; Ribeiro, Leonardo F. R.. - : Association for Computational Linguistics, 2020 BASE Show details 10 From zero to hero: On the limitations of zero-shot language transfer with multilingual transformers Ravishankar, Vinit; Glavaš, Goran; Lauscher, Anne. - : Association for Computational Linguistics, 2020 BASE Show details 11 Specializing Unsupervised Pretraining Models for Word-Level Semantic Similarity ... Lauscher, Anne; Vulić, Ivan; Ponti, Edoardo Maria; Korhonen, Anna; Glavaš, Goran. - : arXiv, 2019 Abstract: Unsupervised pretraining models have been shown to facilitate a wide range of downstream NLP applications. These models, however, retain some of the limitations of traditional static word embeddings. In particular, they encode only the distributional knowledge available in raw text corpora, incorporated through language modeling objectives. In this work, we complement such distributional knowledge with external lexical knowledge, that is, we integrate the discrete knowledge on word-level semantic similarity into pretraining. To this end, we generalize the standard BERT model to a multi-task learning setting where we couple BERT's masked language modeling and next sentence prediction objectives with an auxiliary task of binary word relation classification. Our experiments suggest that our "Lexically Informed" BERT (LIBERT), specialized for the word-level semantic similarity, yields better performance than the lexically blind "vanilla" BERT on several language understanding tasks. Concretely, LIBERT ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://arxiv.org/abs/1909.02339 https://dx.doi.org/10.48550/arxiv.1909.02339 BASE Hide details 12 Informing unsupervised pretraining with external linguistic knowledge Lauscher, Anne; Vulić, Ivan; Ponti, Edoardo Maria. - : Cornell University, 2019 BASE Show details

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