Word-level Language Modeling
Word-Level Language Modeling is a type of language modeling that operates at the word level, where the fundamental unit of analysis and prediction is the word, distinguishing it from character-level or subword-level approaches by treating whole words as the atomic tokens in the probabilistic modeling of natural language.
98
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7.3K
Citations
313
Authors
117
Institutions
Publications per year
2017–2026
52
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98
Character-Aware Neural Language Models
Yoon Kim, Yacine Jernite, David Sontag et al. · Proceedings of the AAAI Conference on Artificial Intelligence · 2016 · 1K citations · Full text
Computing, Computer Science, French +17
Character-Aware Neural Language Models
Yoon Kim, Yacine Jernite, David Sontag et al. · arXiv (Cornell University) · 2015 · 1K citations · Full text
Computing, Computer Science, French +17
Philipp Koehn, Hieu Hoang · Edinburgh Research Explorer (University of Edinburgh) · 2007 · 510 citations · Full text
Code Mixing: A Challenge for Language Identification in the Language of Social Media
Utsab Barman, Amitava Das, Joachim Wagner et al. · 2014 · 271 citations · Full text
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117
University of Cambridge
Cambridge, United Kingdom
5 h-index
14 publications
605 citations
RWTH Aachen University
Aachen, Germany
4 h-index
18 publications
1K citations
Carnegie Mellon University
Pittsburgh, United States
4 h-index
10 publications
402 citations
Microsoft Research (United Kingdom)
Cambridge, United Kingdom
3 h-index
9 publications
604 citations
Microsoft (United States)
Redmond, United States
3 h-index
8 publications
223 citations

Amrita Vishwa Vidyapeetham
Coimbatore, India
3 h-index
9 publications
253 citations
KU Leuven
Leuven, Belgium
2 h-index
8 publications
236 citations
New York University
New York, United States
2 h-index
6 publications
2.3K citations
1–8 of 117
Repository · 18 publications · 2.1K citations
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Conference · 3 publications · 56 citations
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2 publications · 114 citations
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Conference · 2 publications · 79 citations
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