Demonstration Alignment is a methodological framework within Learning from Demonstration that establishes correspondences between temporally misaligned or structurally heterogeneous demonstrations to enable coherent policy learning.
3
Publications
37
Citations
12
Authors
8
Institutions
Publications per year
2017–2026
3
Parents
Publications
3
Domain Adaptive Imitation Learning
Kuno Kim, Yihong Gu, Jiaming Song et al. · arXiv (Cornell University) · 2019 · 12 citations · Full text
Robustness of Demonstration-based Learning Under Limited Data Scenario
Hongxin Zhang, Yanzhe Zhang, Ruiyi Zhang et al. · 2022 · 10 citations · Full text
1–3 of 3
Authors
12
- HZ
1
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- RZ
1
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- JS
1
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- YZ
1
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- SE
1
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1–5 of 12
Institutions
8
Stanford University
Stanford, United States
2 h-index
4 publications
46 citations
Adobe Systems (United States)
San Jose, United States
1 h-index
1 publications
10 citations
Georgia Institute of Technology
Atlanta, United States
1 h-index
1 publications
10 citations
Corvallis Environmental Center
Corvallis, United States
1 h-index
3 publications
45 citations
Shanghai Jiao Tong University
Shanghai, China
1 h-index
1 publications
10 citations
Idiap Research Institute
Martigny-Combe, Switzerland
1 h-index
3 publications
45 citations
Stanford Medicine
Stanford, United States
1 h-index
1 publications
12 citations
Tsinghua University
Beijing, China
1 h-index
1 publications
12 citations
1–8 of 8
Venues
- arXiv (Cornell University)
Repository · 1 publications · 12 citations
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1–1