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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 Hits 1 – 20 of 28 1 Specializing unsupervised pretraining models for word-level semantic similarity Lauscher, Anne [Verfasser]; Vulic, Ivan [Verfasser]; Ponti, Edoardo Maria [Verfasser]. - Mannheim : Universitätsbibliothek Mannheim, 2021 DNB Subject Category Language Show details 2 Towards Zero-shot Language Modeling ... Ponti, Edoardo Maria; Vulić, Ivan; Cotterell, Ryan. - : arXiv, 2021 BASE Show details 3 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 4 Learning Domain-Specialised Representations for Cross-Lingual Biomedical Entity Linking ... Liu, Fangyu; Vulić, Ivan; Korhonen, Anna. - : arXiv, 2021 BASE Show details 5 Combining Deep Generative Models and Multi-lingual Pretraining for Semi-supervised Document Classification ... Zhu, Yi; Shareghi, Ehsan; Li, Yingzhen. - : arXiv, 2021 BASE Show details 6 MirrorWiC: On Eliciting Word-in-Context Representations from Pretrained Language Models ... Liu, Qianchu; Liu, Fangyu; Collier, Nigel. - : arXiv, 2021 BASE Show details 7 Parameter space factorization for zero-shot learning across tasks and languages ... Ponti, Edoardo M.; Vulić, Ivan; Cotterell, Ryan. - : ETH Zurich, 2021 BASE Show details 8 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 9 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. - : Underline Science Inc., 2021 BASE Show details 10 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 11 Semantic Data Set Construction from Human Clustering and Spatial Arrangement ... Majewska, Olga; McCarthy, Diana; Van Den Bosch, Jasper JF. - : Apollo - University of Cambridge Repository, 2021 BASE Show details 12 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 13 Context vs Target Word: Quantifying Biases in Lexical Semantic Datasets ... Liu, Qianchu; McCarthy, Diana; Korhonen, Anna. - : arXiv, 2021 Abstract: State-of-the-art contextualized models such as BERT use tasks such as WiC and WSD to evaluate their word-in-context representations. This inherently assumes that performance in these tasks reflect how well a model represents the coupled word and context semantics. This study investigates this assumption by presenting the first quantitative analysis (using probing baselines) on the context-word interaction being tested in major contextual lexical semantic tasks. Specifically, based on the probing baseline performance, we propose measures to calculate the degree of context or word biases in a dataset, and plot existing datasets on a continuum. The analysis shows most existing datasets fall into the extreme ends of the continuum (i.e. they are either heavily context-biased or target-word-biased) while only AM$^2$iCo and Sense Retrieval challenge a model to represent both the context and target words. Our case study on WiC reveals that human subjects do not share models' strong context biases in the dataset ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://dx.doi.org/10.48550/arxiv.2112.06733 https://arxiv.org/abs/2112.06733 BASE Hide details 14 AM2iCo: Evaluating Word Meaning in Context across Low-Resource Languages with Adversarial Examples ... Liu, Qianchu; Ponti, Edoardo M.; McCarthy, Diana. - : arXiv, 2021 BASE Show details 15 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 16 Parameter space factorization for zero-shot learning across tasks and languages Parovic, Marinela; Cotterell, Ryan; Vulić, Ivan... In: Transactions of the Association for Computational Linguistics, 9 (2021) BASE Show details 17 AM2iCo: Evaluating Word Meaning in Context across Low-Resource Languages with Adversarial Examples ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Korhonen, Anna; Liu, Qianchu. - : Underline Science Inc., 2021 BASE Show details 18 Fast, Effective, and Self-Supervised: Transforming Masked Language Models into Universal Lexical and Sentence Encoders ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Nigel; Korhonen, Anna. - : Underline Science Inc., 2021 BASE Show details 19 Improving Machine Translation of Rare and Unseen Word Senses ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Dario; Fraser, Alexander. - : Underline Science Inc., 2021 BASE Show details 20 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 Page: 1 2

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