Resource-poor Language Processing
Resource-Poor Language Processing is a subfield of Multilingual Natural Language Processing that focuses on developing computational methods, models, or resources for languages with limited availability of annotated data, digital text, or linguistic tools, thereby distinguishing it from approaches designed for well-resourced languages.
162
Publications
8K
Citations
609
Authors
208
Institutions
Publications per year
2017–2026
87
162
Proceedings of the International Conference on Language Resources and Evaluation (LREC)
Wolodja Wentland, Johannes Knopp, Carina Silberer et al. · 2008 · 664 citations
1–5 of 162
609
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3
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208
Carnegie Mellon University
Pittsburgh, United States
7 h-index
33 publications
2.2K citations
Google (United States)
Mountain View, United States
5 h-index
10 publications
1K citations
KU Leuven
Leuven, Belgium
4 h-index
6 publications
103 citations
New York University
New York, United States
4 h-index
7 publications
211 citations
National University of Singapore
Singapore, Singapore
4 h-index
6 publications
255 citations
University of Southern California
Los Angeles, United States
4 h-index
21 publications
648 citations
University of Washington
Seattle, United States
3 h-index
6 publications
242 citations

Indian Institute of Technology Bombay
Mumbai, India
3 h-index
3 publications
47 citations
1–8 of 208
Repository · 9 publications · 222 citations
9
h-index
7 publications · 252 citations
7
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Conference · 4 publications · 213 citations
4
h-index
3 publications · 62 citations
3
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TACL · 3 publications · 323 citations
3
h-index
1–5