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In-N-Out: Pre-Training and Self-Training using Auxiliary Information for
  Out-of-Distribution Robustness

In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness

8 December 2020
Sang Michael Xie
Ananya Kumar
Robbie Jones
Fereshte Khani
Tengyu Ma
Percy Liang
    OOD
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Papers citing "In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness"

12 / 12 papers shown
Title
Out-of-distribution Generalization for Total Variation based Invariant Risk Minimization
Out-of-distribution Generalization for Total Variation based Invariant Risk Minimization
Yuanchao Wang
Zhao-Rong Lai
Tianqi Zhong
71
1
0
27 Feb 2025
Distribution Shifts at Scale: Out-of-distribution Detection in Earth Observation
Distribution Shifts at Scale: Out-of-distribution Detection in Earth Observation
Burak Ekim
G. Tadesse
Caleb Robinson
G. Q. Hacheme
Michael Schmitt
Rahul Dodhia
J. L. Ferres
OODD
95
1
0
18 Dec 2024
LEVI: Generalizable Fine-tuning via Layer-wise Ensemble of Different
  Views
LEVI: Generalizable Fine-tuning via Layer-wise Ensemble of Different Views
Yuji Roh
Qingyun Liu
Huan Gui
Zhe Yuan
Yujin Tang
...
Liang Liu
Shuchao Bi
Lichan Hong
Ed H. Chi
Zhe Zhao
43
1
0
07 Feb 2024
Beyond Concept Bottleneck Models: How to Make Black Boxes Intervenable?
Beyond Concept Bottleneck Models: How to Make Black Boxes Intervenable?
Sonia Laguna
Ricards Marcinkevics
Moritz Vandenhirtz
Julia E. Vogt
25
17
0
24 Jan 2024
Preserving Silent Features for Domain Generalization
Preserving Silent Features for Domain Generalization
Chujie Zhao
Tianren Zhang
Feng Chen
23
0
0
06 Jan 2024
Backdoor Learning for NLP: Recent Advances, Challenges, and Future
  Research Directions
Backdoor Learning for NLP: Recent Advances, Challenges, and Future Research Directions
Marwan Omar
SILM
AAML
25
20
0
14 Feb 2023
Surgical Fine-Tuning Improves Adaptation to Distribution Shifts
Surgical Fine-Tuning Improves Adaptation to Distribution Shifts
Yoonho Lee
Annie S. Chen
Fahim Tajwar
Ananya Kumar
Huaxiu Yao
Percy Liang
Chelsea Finn
OOD
51
197
0
20 Oct 2022
Towards Understanding GD with Hard and Conjugate Pseudo-labels for
  Test-Time Adaptation
Towards Understanding GD with Hard and Conjugate Pseudo-labels for Test-Time Adaptation
Jun-Kun Wang
Andre Wibisono
29
7
0
18 Oct 2022
Calibrated ensembles can mitigate accuracy tradeoffs under distribution
  shift
Calibrated ensembles can mitigate accuracy tradeoffs under distribution shift
Ananya Kumar
Tengyu Ma
Percy Liang
Aditi Raghunathan
UQCV
OODD
OOD
39
38
0
18 Jul 2022
Fishr: Invariant Gradient Variances for Out-of-Distribution
  Generalization
Fishr: Invariant Gradient Variances for Out-of-Distribution Generalization
Alexandre Ramé
Corentin Dancette
Matthieu Cord
OOD
38
204
0
07 Sep 2021
Can Subnetwork Structure be the Key to Out-of-Distribution
  Generalization?
Can Subnetwork Structure be the Key to Out-of-Distribution Generalization?
Dinghuai Zhang
Kartik Ahuja
Yilun Xu
Yisen Wang
Aaron Courville
OOD
20
95
0
05 Jun 2021
Cycle Self-Training for Domain Adaptation
Cycle Self-Training for Domain Adaptation
Hong Liu
Jianmin Wang
Mingsheng Long
25
174
0
05 Mar 2021
1