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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 72 1 HistBERT: A Pre-trained Language Model for Diachronic Lexical Semantic Analysis ... Qiu, Wenjun; Xu, Yang. - : arXiv, 2022 BASE Show details 2 Neural reality of argument structure constructions ... Li, Bai; Zhu, Zining; Thomas, Guillaume. - : arXiv, 2022 BASE Show details 3 HistBERT: A Pre-trained Language Model for Diachronic Lexical Semantic Analysis ... Wenjun Qiu; Xu, Yang. - : Unpublished, 2022 BASE Show details 4 Computational approaches to semantic change Tahmasebi, Nina N. (Herausgeber); Borin, Lars (Herausgeber); Jatowt, Adam (Herausgeber). - Berlin : Language Science Press, 2021 UB Frankfurt Linguistik Show details 5 Chaining and the formation of spatial semantic categories in childhood Xu, Aotao; Xu, Yang In: Proceedings of the Annual Meeting of the Cognitive Science Society, vol 43, iss 43 (2021) BASE Show details 6 A computational evaluation of gender asymmetry in semantic change Schnell, Eric; Xu, Yang In: Proceedings of the Annual Meeting of the Cognitive Science Society, vol 43, iss 43 (2021) BASE Show details 7 A diachronic evaluation of gender asymmetry in euphemism ... Kapron-King, Anna; Xu, Yang. - : arXiv, 2021 BASE Show details 8 Teachers and Students Enacting Language Policy: A Case Study of a Secondary School in China ... Xu, Yang. - : The Australian National University, 2021 BASE Show details 9 Computational approaches to semantic change ... Tahmasebi, Nina; Borin, Lars; Jatowt, Adam. - : Zenodo, 2021 BASE Show details 10 Computational approaches to semantic change ... Tahmasebi, Nina; Borin, Lars; Jatowt, Adam. - : Zenodo, 2021 BASE Show details 11 LayoutLMv2: Multi-modal Pre-training for Visually-rich Document Understanding ... 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; Che, Wanxiang; Cui, Lei. - : Underline Science Inc., 2021 BASE Show details 12 A computational evaluation of gender asymmetry in semantic change ... 43rd Annual Meeting of the Cognitive Science Society 2021; Schnell, Eric; Xu, Yang. - : Underline Science Inc., 2021 BASE Show details 13 A computational evaluation of gender asymmetry in semantic change ... 43rd Annual Meeting of the Cognitive Science Society 2021; Schnell, Eric; Xu, Yang. - : Underline Science Inc., 2021 BASE Show details 14 Predicting emergent linguistic compositions through time: Syntactic frame extension via multimodal chaining ... Yu, Lei; Xu, Yang. - : arXiv, 2021 BASE Show details 15 Chaining algorithms and historical adjective extension ... Grewal, Karan; Xu, Yang. - : Zenodo, 2021 BASE Show details 16 Chaining algorithms and historical adjective extension ... Grewal, Karan; Xu, Yang. - : Zenodo, 2021 BASE Show details 17 Historical changes in semantic weights of sub-word units ... Xu, Yang; Zhang, Zheng-Sheng. - : Zenodo, 2021 Abstract: In this chapter, we present a computational study on how the weight of sub-word units in determining word meanings evolves chronologically in different languages. Sub-word units, e.g., morphemes, syllables etc., play variable roles in determining word meanings. Some morphemes in English have standalone lexical meanings (e.g., the root) while others function more as morpho-syntactic markers (e.g., the bound morphemes such as -ness etc.) The semantic weight of sub-word units changes over time; for instance, some ancient characters in Chinese or ancient prefixes in English no longer carry clear semantic meanings. The goal of this chapter is to characterize such a change with computational methods. The semantic weight of sub-word units can be captured by word embedding models (and their variants). We present results from two substudies. In Study 1, we propose a novel neural network-based word embedding model to model the semantic weights from sub-word units. We draw a comparison between Chinese and Indo-European ... URL: https://zenodo.org/record/5040310 https://dx.doi.org/10.5281/zenodo.5040310 BASE Hide details 18 Historical changes in semantic weights of sub-word units ... Xu, Yang; Zhang, Zheng-Sheng. - : Zenodo, 2021 BASE Show details 19 Chaining and the formation of spatial semantic categories in childhood ... 43rd Annual Meeting of the Cognitive Science Society 2021; Xu, Yang; Xu, Aotao John. - : Underline Science Inc., 2021 BASE Show details 20 Predicting emergent linguistic compositions through time: Syntactic frame extension via multimodal chaining ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Xu, Yang; Yu, Lei. - : Underline Science Inc., 2021 BASE Show details Page: 1 2 3 4

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