Static Word Embeddings
Static Word Embeddings is a type of word representation in natural language processing where each word is mapped to a fixed-dimensional vector in a continuous space, learned from corpus statistics and remaining invariant across different linguistic contexts.
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3.9K
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258
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119
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2017–2026
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A survey of word embeddings based on deep learning
Shirui Wang, Wenan Zhou, Chao Jiang · Computing · 2019 · 191 citations
Multi-task learning based pre-trained language model for code completion
Fang Liu, Ge Li, Yunfei Zhao et al. · 2020 · 162 citations
Joint embedding VQA model based on dynamic word vector
Zhiyang Ma, Wenfeng Zheng, Xiaobing Chen et al. · PeerJ Computer Science · 2021 · 149 citations · Full text
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University of Cambridge
Cambridge, United Kingdom
3 h-index
11 publications
265 citations
Laboratoire d'Informatique pour la Mécanique et les Sciences de l'Ingénieur
Orsay, France
3 h-index
7 publications
230 citations

Centre National de la Recherche Scientifique
Paris, France
3 h-index
8 publications
309 citations

Harbin Institute of Technology
Harbin, China
2 h-index
10 publications
400 citations

Zhejiang University
Hangzhou, China
2 h-index
3 publications
78 citations
National University of Singapore
Singapore, Singapore
2 h-index
4 publications
64 citations
Université Paris-Sud
Orsay, France
2 h-index
6 publications
219 citations
University of Utah
Salt Lake City, United States
2 h-index
8 publications
452 citations
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Repository · 8 publications · 255 citations
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TASLP · 2 publications · 48 citations
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2 publications · 31 citations
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2 publications · 88 citations
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TACL · 2 publications · 85 citations
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