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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 Hits 1 – 20 of 68 1 Improving Word Translation via Two-Stage Contrastive Learning ... Li, Yaoyiran; Liu, Fangyu; Collier, Nigel. - : arXiv, 2022 BASE Show details 2 Plan-then-Generate: Controlled Data-to-Text Generation via Planning ... Su, Yixuan; Vandyke, David; Wang, Sihui. - : arXiv, 2021 BASE Show details 3 Prix-LM: Pretraining for Multilingual Knowledge Base Construction ... Zhou, Wenxuan; Liu, Fangyu; Vulić, Ivan. - : arXiv, 2021 BASE Show details 4 Learning Domain-Specialised Representations for Cross-Lingual Biomedical Entity Linking ... Liu, Fangyu; Vulić, Ivan; Korhonen, Anna. - : arXiv, 2021 BASE Show details 5 MirrorWiC: On Eliciting Word-in-Context Representations from Pretrained Language Models ... Liu, Qianchu; Liu, Fangyu; Collier, Nigel. - : arXiv, 2021 BASE Show details 6 MirrorWiC: On Eliciting Word-in-Context Representations from Pretrained Language Models ... Liu, Qianchu; Liu, Fangyu; Collier, Nigel. - : Apollo - University of Cambridge Repository, 2021 BASE Show details 7 Visually Grounded Reasoning across Languages and Cultures ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Bugliarello, Emanuele; Collier, Nigel. - : Underline Science Inc., 2021 BASE Show details 8 Fast, Effective, and Self-Supervised: Transforming Masked Language Models into Universal Lexical and Sentence Encoders ... Liu, Fangyu; Vulić, I; Korhonen, Anna-Leena; Collier, Nigel. - : Apollo - University of Cambridge Repository, 2021 Abstract: Pretrained Masked Language Models (MLMs) have revolutionised NLP in recent years. However, previous work has indicated that off-the-shelf MLMs are not effective as universal lexical or sentence encoders without further task-specific fine-tuning on NLI, sentence similarity, or paraphrasing tasks using annotated task data. In this work, we demonstrate that it is possible to turn MLMs into effective universal lexical and sentence encoders even without any additional data and without any supervision. We propose an extremely simple, fast and effective contrastive learning technique, termed Mirror-BERT, which converts MLMs (e.g., BERT and RoBERTa) into such encoders in 20-30 seconds without any additional external knowledge. Mirror-BERT relies on fully identical or slightly modified string pairs as positive (i.e., synonymous) fine-tuning examples, and aims to maximise their similarity during identity fine-tuning. We report huge gains over off-the-shelf MLMs with Mirror-BERT in both lexical-level and sentence-level ... Keyword: cs.AI; cs.CL; cs.LG URL: https://www.repository.cam.ac.uk/handle/1810/327954 https://dx.doi.org/10.17863/cam.75407 BASE Hide details 9 Visually Grounded Reasoning across Languages and Cultures ... Liu, Fangyu; Bugliarello, Emanuele; Ponti, Edoardo Maria. - : arXiv, 2021 BASE Show details 10 Fast, Effective, and Self-Supervised: Transforming Masked Language Models into Universal Lexical and Sentence Encoders ... Liu, Fangyu; Vulić, Ivan; Korhonen, Anna. - : arXiv, 2021 BASE Show details 11 Self-Alignment Pretraining for Biomedical Entity Representations Liu, Fangyu; Shareghi, Ehsan; Meng, Zaiqiao. - : Association for Computational Linguistics, 2021. : Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021 BASE Show details 12 Large-scale exploration of neural relation classification architectures ... Le, HQ; Can, DC; Vu, ST. - : Apollo - University of Cambridge Repository, 2020 BASE Show details 13 Will-They-Won't-They: A Very Large Dataset for Stance Detection on Twitter ... Conforti, Costanza; Berndt, Jakob; Pilehvar, Mohammad Taher. - : Apollo - University of Cambridge Repository, 2020 BASE Show details 14 A pragmatic guide to geoparsing evaluation Gritta, Milan; Pilehvar, Mohammad Taher; Collier, Nigel. - : Springer Netherlands, 2020. : Language Resources and Evaluation, 2020 BASE Show details 15 Will-They-Won't-They: A Very Large Dataset for Stance Detection on Twitter Conforti, Costanza; Berndt, Jakob; Pilehvar, Mohammad Taher. - : 58TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL 2020), 2020 BASE Show details 16 STANDER: An expert-annotated dataset for news stance detection and evidence retrieval Conforti, C; Berndt, J; Pilehvar, MT. - : Association for Computational Linguistics, 2020. : Findings of the Association for Computational Linguistics Findings of ACL: EMNLP 2020, 2020 BASE Show details 17 Large-scale exploration of neural relation classification architectures Le, HQ; Can, DC; Vu, ST. - : Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018, 2020 BASE Show details 18 A pragmatic guide to geoparsing evaluation : Toponyms, Named Entity Recognition and pragmatics [<Journal>] Gritta, Milan [Verfasser]; Pilehvar, Mohammad Taher [Verfasser]; Collier, Nigel [Verfasser] DNB Subject Category Language Show details 19 A Pragmatic Guide to Geoparsing Evaluation ... Gritta, Milan; Collier, Nigel; Pilehvar, Mohammad. - : Apollo - University of Cambridge Repository, 2019 BASE Show details 20 A pragmatic guide to geoparsing evaluation ... Gritta, Milan; Pilehvar, Mohammad Taher; Collier, Nigel. - : Apollo - University of Cambridge Repository, 2019 BASE Show details Page: 1 2 3 4

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