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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 – 7 of 7 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 UNKs Everywhere: Adapting Multilingual Language Models to New Scripts ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Iryna; ., Sebastian. - : Underline Science Inc., 2021 BASE Show details 3 How Good is Your Tokenizer? On the Monolingual Performance of Multilingual 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; ., Iryna; ., Sebastian. - : Underline Science Inc., 2021 BASE Show details 4 Learning Domain-Specialised Representations for Cross-Lingual Biomedical Entity Linking ... 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; ., Nigel; Korhonen, Anna; Liu, Fangyu; Vulić, Ivan. - : Underline Science Inc., 2021 Abstract: Read paper: https://www.aclanthology.org/2021.acl-short.72 Abstract: Injecting external domain-specific knowledge (e.g., UMLS) into pretrained language models (LMs) advances their capability to handle specialised in-domain tasks such as biomedical entity linking (BEL). However, such abundant expert knowledge is available only for a handful of languages (e.g., English). In this work, by proposing a novel cross-lingual biomedical entity linking task (XL-BEL) and establishing a new XL-BEL benchmark spanning 10 typologically diverse languages, we first investigate the ability of standard knowledge-agnostic as well as knowledge-enhanced monolingual and multilingual LMs beyond the standard monolingual English BEL task. The scores indicate large gaps to English performance. We then address the challenge of transferring domain-specific knowledge in resource-rich languages to resource-poor ones. To this end, we propose and evaluate a series of cross-lingual transfer methods for the XL-BEL task, and demonstrate that ... Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics URL: https://underline.io/lecture/25632-learning-domain-specialised-representations-for-cross-lingual-biomedical-entity-linking https://dx.doi.org/10.48448/v8cn-0854 BASE Hide details 5 MirrorWiC: On Eliciting Word-in-Context Representations from Pretrained Language Models ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Nigel; Korhonen, Anna. - : Underline Science Inc., 2021 BASE Show details 6 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 7 A Closer Look at Few-Shot Crosslingual Transfer: The Choice of Shots Matters ... 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; ., Hinrich; Korhonen, Anna. - : Underline Science Inc., 2021 BASE Show details

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