Markov Language Models
Markov Language Models is a type of probabilistic language model that assumes the probability of each word in a sequence depends only on a fixed number of preceding words, formalized through the Markov property to simplify joint probability estimation in natural language.
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23K
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503
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182
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Publications per year
2017–2026
25
Variants
Markov Language Model
Parents
212
Discriminative training methods for hidden Markov models
Michael Collins · 2002 · 1.9K citations · Full text
Thorsten Brants · 2000 · 1.3K citations · Full text
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AT&T (United States)
Bedminster, United States
6 h-index
11 publications
2.9K citations
University of Washington
Seattle, United States
5 h-index
8 publications
204 citations
Universitat Politècnica de València
Valencia, Spain
4 h-index
10 publications
268 citations
Stanford University
Stanford, United States
4 h-index
12 publications
10.3K citations
IBM Research - Thomas J. Watson Research Center
Yorktown Heights, United States
4 h-index
14 publications
2.7K citations

National Taiwan University
Taipei, Taiwan
4 h-index
16 publications
3.8K citations
Korea University
Seoul, South Korea
4 h-index
6 publications
168 citations
Purdue University West Lafayette
West Lafayette, United States
3 h-index
6 publications
442 citations
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9 publications · 328 citations
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TPAMI · 4 publications · 1.1K citations
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4 publications · 154 citations
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Repository · 3 publications · 177 citations
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Conference · 2 publications · 60 citations
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