Attention Head Pruning
Attention Head Pruning is a model compression technique that selectively removes redundant or less informative attention heads from a transformer architecture to improve computational efficiency while preserving model performance.
16
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2K
Citations
52
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23
Institutions
Publications per year
2017–2026
16
Parents
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When BERT Plays the Lottery, All Tickets Are Winning
Sai Prasanna, Anna Rogers, Anna Rumshisky · 2020 · 115 citations · Full text
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University of Amsterdam
Amsterdam, The Netherlands
2 h-index
4 publications
2.3K citations

University of Edinburgh
Edinburgh, United Kingdom
2 h-index
4 publications
2.2K citations

Moscow Institute of Physics and Technology
Dolgoprudnyy, Russia
2 h-index
2 publications
1.1K citations
Massachusetts Institute of Technology
Cambridge, United States
2 h-index
6 publications
1.2K citations
University of Zurich
Zurich, Switzerland
2 h-index
2 publications
1.1K citations
Google (United States)
Mountain View, United States
1 h-index
5 publications
160 citations
University of Massachusetts Lowell
Lowell, United States
1 h-index
3 publications
345 citations
Harvard University
Cambridge, United States
1 h-index
5 publications
160 citations
1–8 of 23
Repository · 5 publications · 190 citations
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1 publications · 34 citations
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1 publications · 23 citations
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TVCG · 1 publications · 41 citations
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Repository · 1 publications · 70 citations
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