Controllable Generation
Controllable Generation is a generative modeling framework that enables explicit manipulation of specific attributes or features in the output by conditioning the generation process on user-defined control signals.
207
Publications
14.9K
Citations
841
Authors
265
Institutions
Publications per year
2017–2026
156
207
Lucas Kovar, Michael Gleicher, Frédéric Pighin · 2008 · 1.1K citations
Md. Sajibul Alam Bhuyan, Md. Nizam Uddin, Md. Maksudul Islam et al. · International nano letters. · 2016 · 719 citations · Full text
Natural Sciences, Materials Engineering, Materials Science +14
Chong Mou, Xintao Wang, Liangbin Xie et al. · Proceedings of the AAAI Conference on Artificial Intelligence · 2024 · 718 citations · Full text
Lucas Kovar, Michael Gleicher, Frédéric Pighin · ACM Transactions on Graphics · 2002 · 591 citations
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265
Tsinghua University
Beijing, China
12 h-index
37 publications
1.5K citations
University of Science and Technology of China
Hefei, China
6 h-index
25 publications
1.8K citations

Chinese Academy of Sciences
Beijing, China
5 h-index
20 publications
1.4K citations
Chinese University of Hong Kong
Hong Kong, Hong Kong
5 h-index
13 publications
595 citations
Carnegie Mellon University
Pittsburgh, United States
5 h-index
18 publications
1K citations
University of Wisconsin–Madison
Madison, United States
5 h-index
9 publications
4.2K citations
University of Washington
Seattle, United States
5 h-index
11 publications
901 citations

Hong Kong University of Science and Technology
Hong Kong, Hong Kong
4 h-index
9 publications
574 citations
1–8 of 265
Repository · 51 publications · 2.8K citations
24
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4 publications · 145 citations
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Conference · 4 publications · 959 citations
4
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4 publications · 448 citations
4
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PRA · 3 publications · 62 citations
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