Auxiliary Task Learning
Auxiliary Task Learning is a multi-task learning strategy in which an auxiliary task, distinct from the primary task, is introduced to improve model performance by providing additional inductive bias through shared representations.
348
Publications
55.8K
Citations
1.3K
Authors
383
Institutions
Publications per year
2017–2026
333
Parents
348
Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
Ross Girshick, Jeff Donahue, Trevor Darrell et al. · 2014 · 31.8K citations
VectorNet: Encoding HD Maps and Agent Dynamics From Vectorized Representation
Jiyang Gao, Chen Sun, Hang Zhao et al. · 2020 · 898 citations
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University of Chinese Academy of Sciences
Beijing, China
14 h-index
55 publications
2K citations
Google (United States)
Mountain View, United States
13 h-index
63 publications
5.6K citations

Chinese Academy of Sciences
Beijing, China
10 h-index
46 publications
1.5K citations

Peking University
Beijing, China
8 h-index
18 publications
617 citations
Carnegie Mellon University
Pittsburgh, United States
8 h-index
16 publications
1.5K citations
University of Science and Technology of China
Hefei, China
8 h-index
23 publications
1.5K citations
Nanyang Technological University
Singapore, Singapore
8 h-index
16 publications
1.1K citations
Tsinghua University
Beijing, China
8 h-index
32 publications
1.3K citations
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Repository · 49 publications · 5K citations
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Conference · 20 publications · 1.8K citations
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12 publications · 410 citations
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