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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; Elliott, Desmond; Liu, Fangyu; Maria Ponti, Edoardo; Reddy, Siva. - : Underline Science Inc., 2021 Abstract: Anthology paper link: https://aclanthology.org/2021.emnlp-main.818/ Abstract: The design of widespread vision-and-language datasets and pre-trained encoders directly adopts, or draws inspiration from, the concepts and images of ImageNet. While one can hardly overestimate how much this benchmark contributed to progress in computer vision, it is mostly derived from lexical databases and image queries in English, resulting in source material with a North American or Western European bias. Therefore, we devise a new protocol to construct an ImageNet-style hierarchy representative of more languages and cultures. In particular, we let the selection of both concepts and images be entirely driven by native speakers, rather than scraping them automatically. Specifically, we focus on a typologically diverse set of languages, namely, Indonesian, Mandarin Chinese, Swahili, Tamil, and Turkish. On top of the concepts and images obtained through this new protocol, we create a multilingual dataset for {M}ulticultur{a}l ... Keyword: Computer programming; Intelligent System; Machine Learning; Machine translation; Natural Language Processing; Sentiment Analysis URL: https://dx.doi.org/10.48448/yncc-sm24 https://underline.io/lecture/38942-visually-grounded-reasoning-across-languages-and-cultures BASE Hide details 8 Fast, Effective, and Self-Supervised: Transforming Masked Language Models into Universal Lexical and Sentence Encoders ... Liu, Fangyu; Vulić, I; Korhonen, Anna-Leena. - : Apollo - University of Cambridge Repository, 2021 BASE Show 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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