Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
2112.05090
Cited By
v1
v2 (latest)
Extending the WILDS Benchmark for Unsupervised Adaptation
9 December 2021
Shiori Sagawa
Pang Wei Koh
Tony Lee
Irena Gao
Sang Michael Xie
Kendrick Shen
Ananya Kumar
Weihua Hu
Michihiro Yasunaga
Henrik Marklund
Sara Beery
Etienne David
Ian Stavness
Wei Guo
J. Leskovec
Kate Saenko
Tatsunori Hashimoto
Sergey Levine
Chelsea Finn
Abigail Z. Jacobs
OOD
Re-assign community
ArXiv (abs)
PDF
HTML
HuggingFace (1 upvotes)
Papers citing
"Extending the WILDS Benchmark for Unsupervised Adaptation"
50 / 80 papers shown
Domain Generalization: A Tale of Two ERMs
Yilun Zhu
Naihao Deng
Naichen Shi
Aditya Gangrade
Clayton Scott
OOD
111
0
0
06 Oct 2025
Confidence and Dispersity as Signals: Unsupervised Model Evaluation and Ranking
Weijian Deng
Weijie Tu
Ibrahim Radwan
Mohammad Abu Alsheikh
Stephen Gould
Liang Zheng
131
0
0
03 Oct 2025
FedDAPL: Toward Client-Private Generalization in Federated Learning
Soroosh Safari Loaliyan
J. Ambite
Paul M. Thompson
N. Jahanshad
Greg Ver Steeg
OOD
FedML
AI4CE
158
0
0
28 Sep 2025
Unsupervised Domain Adaptation for Binary Classification with an Unobservable Source Subpopulation
Chao Ying
Jun Jin
H. Zhang
Qinglong Tian
Yanyuan Ma
Yixuan Li
Jiwei Zhao
OOD
289
0
0
24 Sep 2025
Improving Out-of-Domain Robustness with Targeted Augmentation in Frequency and Pixel Spaces
Ruoqi Wang
Haitao Wang
Shaojie Guo
Qiong Luo
OOD
275
0
0
18 May 2025
Robustness to Geographic Distribution Shift Using Location Encoders
Ruth Crasto
OOD
277
0
0
03 Mar 2025
Are nuclear masks all you need for improved out-of-domain generalisation? A closer look at cancer classification in histopathology
Neural Information Processing Systems (NeurIPS), 2024
Dhananjay Tomar
Alexander Binder
Andreas Kleppe
262
1
0
14 Nov 2024
Contrastive ground-level image and remote sensing pre-training improves representation learning for natural world imagery
European Conference on Computer Vision (ECCV), 2024
Andy V. Huynh
Lauren E. Gillespie
Jael Lopez-Saucedo
Claire Tang
Rohan Sikand
Moisés Expósito-Alonso
SSL
250
12
0
28 Sep 2024
SKADA-Bench: Benchmarking Unsupervised Domain Adaptation Methods with Realistic Validation On Diverse Modalities
Yanis Lalou
Théo Gnassounou
Antoine Collas
Antoine de Mathelin
Oleksii Kachaiev
Ambroise Odonnat
Alexandre Gramfort
Thomas Moreau
Rémi Flamary
542
1
0
16 Jul 2024
Self-supervised Vision Transformer are Scalable Generative Models for Domain Generalization
Sebastian Doerrich
Francesco Di Salvo
Christian Ledig
MedIm
ViT
132
3
0
03 Jul 2024
Accuracy on the wrong line: On the pitfalls of noisy data for out-of-distribution generalisation
Amartya Sanyal
Yaxi Hu
Yaodong Yu
Yian Ma
Yixin Wang
Bernhard Schölkopf
OODD
216
7
0
27 Jun 2024
Edge Classification on Graphs: New Directions in Topological Imbalance
Xueqi Cheng
Yu Wang
Yunchao Liu
Yuying Zhao
Charu C. Aggarwal
Hanyu Wang
200
7
0
17 Jun 2024
What Does Softmax Probability Tell Us about Classifiers Ranking Across Diverse Test Conditions?
Weijie Tu
Weijian Deng
Liang Zheng
Tom Gedeon
308
4
0
14 Jun 2024
CLIPLoss and Norm-Based Data Selection Methods for Multimodal Contrastive Learning
Yiping Wang
Yifang Chen
Wendan Yan
Alex Fang
Wenjing Zhou
Kevin Jamieson
S. Du
303
15
0
29 May 2024
SCMix: Stochastic Compound Mixing for Open Compound Domain Adaptation in Semantic Segmentation
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2024
Kai Yao
Zhaorui Tan
Zixian Su
Xi Yang
Jie Sun
Kaizhu Huang
298
1
0
23 May 2024
A General Theory for Compositional Generalization
Jingwen Fu
Zhizheng Zhang
Yan Lu
Nanning Zheng
AI4CE
CoGe
241
2
0
20 May 2024
MoVL:Exploring Fusion Strategies for the Domain-Adaptive Application of Pretrained Models in Medical Imaging Tasks
Haijiang Tian
Jingkun Yue
Xiaohong Liu
Guoxing Yang
Zeyu Jiang
Guangyu Wang
VLM
MedIm
274
1
0
13 May 2024
Adapting to Distribution Shift by Visual Domain Prompt Generation
International Conference on Learning Representations (ICLR), 2024
Zhixiang Chi
Li Gu
Tao Zhong
Huan Liu
Yuanhao Yu
Konstantinos N Plataniotis
Yang Wang
VLM
OOD
250
20
0
05 May 2024
ViTamin: Designing Scalable Vision Models in the Vision-Language Era
Computer Vision and Pattern Recognition (CVPR), 2024
Jienneg Chen
Qihang Yu
Xiaohui Shen
Yaoyao Liu
Liang-Chieh Chen
3DV
VLM
411
50
0
02 Apr 2024
Transfer Learning for T-Cell Response Prediction
Josua Stadelmaier
Brandon Malone
Ralf Eggeling
181
0
0
18 Mar 2024
Variance Alignment Score: A Simple But Tough-to-Beat Data Selection Method for Multimodal Contrastive Learning
Yiping Wang
Yifang Chen
Wendan Yan
Kevin Jamieson
S. Du
257
7
0
03 Feb 2024
Good at captioning, bad at counting: Benchmarking GPT-4V on Earth observation data
Chenhui Zhang
Sherrie Wang
283
36
0
31 Jan 2024
AutoFT: Learning an Objective for Robust Fine-Tuning
Caroline Choi
Yoonho Lee
Annie S. Chen
Allan Zhou
Aditi Raghunathan
Chelsea Finn
OOD
321
1
0
18 Jan 2024
Connect Later: Improving Fine-tuning for Robustness with Targeted Augmentations
International Conference on Machine Learning (ICML), 2024
Helen Qu
Sang Michael Xie
264
5
0
08 Jan 2024
Out of the Ordinary: Spectrally Adapting Regression for Covariate Shift
International Conference on Machine Learning (ICML), 2023
Benjamin Eyre
Elliot Creager
David Madras
Antonio Torralba
Katherine Heller
OOD
OODD
212
3
0
29 Dec 2023
Domain constraints improve risk prediction when outcome data is missing
S. Balachandar
Nikhil Garg
Emma Pierson
CML
OOD
330
10
0
06 Dec 2023
Complementary Benefits of Contrastive Learning and Self-Training Under Distribution Shift
Saurabh Garg
Amrith Rajagopal Setlur
Zachary Chase Lipton
Sivaraman Balakrishnan
Virginia Smith
Aditi Raghunathan
SSL
243
12
0
06 Dec 2023
COSTAR: Improved Temporal Counterfactual Estimation with Self-Supervised Learning
Chuizheng Meng
Yihe Dong
Sercan O. Arik
Yan Liu
Tomas Pfister
CML
AI4TS
343
1
0
01 Nov 2023
Assessing and Enhancing Robustness of Deep Learning Models with Corruption Emulation in Digital Pathology
IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2023
Peixiang Huang
Songtao Zhang
Yulu Gan
Rui Xu
Rongqi Zhu
Wenkang Qin
Limei Guo
Shan Jiang
Lin Luo
168
6
0
31 Oct 2023
Gradual Domain Adaptation: Theory and Algorithms
Yifei He
Haoxiang Wang
Bo Li
Han Zhao
CLL
401
17
0
20 Oct 2023
Make the U in UDA Matter: Invariant Consistency Learning for Unsupervised Domain Adaptation
Neural Information Processing Systems (NeurIPS), 2023
Zhongqi Yue
Hanwang Zhang
Qianru Sun
OOD
289
28
0
22 Sep 2023
Learning to Drive Anywhere
Conference on Robot Learning (CoRL), 2023
Ruizhao Zhu
Peng Huang
Eshed Ohn-Bar
Venkatesh Saligrama
356
11
0
21 Sep 2023
Prominent Roles of Conditionally Invariant Components in Domain Adaptation: Theory and Algorithms
Keru Wu
Yuansi Chen
Wooseok Ha
Ting Yu
CML
344
2
0
19 Sep 2023
Test-Time Poisoning Attacks Against Test-Time Adaptation Models
IEEE Symposium on Security and Privacy (IEEE S&P), 2023
Tianshuo Cong
Xinlei He
Yun Shen
Yang Zhang
AAML
TTA
180
10
0
16 Aug 2023
A Holistic Assessment of the Reliability of Machine Learning Systems
Anthony Corso
David Karamadian
Romeo Valentin
Mary Cooper
Mykel J. Kochenderfer
316
10
0
20 Jul 2023
Towards Federated Foundation Models: Scalable Dataset Pipelines for Group-Structured Learning
Neural Information Processing Systems (NeurIPS), 2023
Zachary B. Charles
Nicole Mitchell
Krishna Pillutla
Michael Reneer
Zachary Garrett
FedML
AI4CE
315
33
0
18 Jul 2023
Causality-oriented robustness: exploiting general noise interventions
Xinwei Shen
Peter Buhlmann
Armeen Taeb
OOD
324
11
0
18 Jul 2023
Curious Replay for Model-based Adaptation
International Conference on Machine Learning (ICML), 2023
Isaac Kauvar
Christopher Doyle
Linqi Zhou
Nick Haber
157
16
0
28 Jun 2023
Conservative Prediction via Data-Driven Confidence Minimization
Caroline Choi
Fahim Tajwar
Yoonho Lee
Huaxiu Yao
Ananya Kumar
Chelsea Finn
157
7
0
08 Jun 2023
ContriMix: Scalable stain color augmentation for domain generalization without domain labels in digital pathology
Tan H. Nguyen
Dinkar Juyal
Jin Li
Aaditya (Adi) Prakash
Shima Nofallah
...
Michael Griffin
Anand Sampat
J. Abel
Justin Lee
A. Taylor-Weiner
MedIm
316
6
0
07 Jun 2023
(Almost) Provable Error Bounds Under Distribution Shift via Disagreement Discrepancy
Neural Information Processing Systems (NeurIPS), 2023
Elan Rosenfeld
Saurabh Garg
UQCV
187
12
0
01 Jun 2023
Contextual Vision Transformers for Robust Representation Learning
Yu Bao
Theofanis Karaletsos
ViT
280
14
0
30 May 2023
DataComp: In search of the next generation of multimodal datasets
Neural Information Processing Systems (NeurIPS), 2023
S. Gadre
Gabriel Ilharco
Alex Fang
J. Hayase
Georgios Smyrnis
...
A. Dimakis
J. Jitsev
Y. Carmon
Vaishaal Shankar
Ludwig Schmidt
VLM
629
580
0
27 Apr 2023
ZRG: A Dataset for Multimodal 3D Residential Rooftop Understanding
IEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2023
Isaac Corley
Jonathan Lwowski
Peyman Najafirad
192
0
0
26 Apr 2023
BenchMD: A Benchmark for Unified Learning on Medical Images and Sensors
Kathryn Wantlin
Chenwei Wu
Shih-Cheng Huang
Oishi Banerjee
Farah Z. Dadabhoy
...
A. Adamson
Laura Heacock
G. Tison
Alex Tamkin
Pranav Rajpurkar
SSL
OOD
149
4
0
17 Apr 2023
ASPEST: Bridging the Gap Between Active Learning and Selective Prediction
Jiefeng Chen
Chang Jo Kim
Sayna Ebrahimi
Sercan O. Arik
S. Jha
Tomas Pfister
367
5
0
07 Apr 2023
A New Benchmark: On the Utility of Synthetic Data with Blender for Bare Supervised Learning and Downstream Domain Adaptation
Computer Vision and Pattern Recognition (CVPR), 2023
Hui Tang
Kui Jia
OOD
324
18
0
16 Mar 2023
Diagnosing Model Performance Under Distribution Shift
Tiffany Cai
Hongseok Namkoong
Steve Yadlowsky
561
38
0
03 Mar 2023
Edit at your own risk: evaluating the robustness of edited models to distribution shifts
Davis Brown
Charles Godfrey
Cody Nizinski
Jonathan Tu
Henry Kvinge
KELM
246
8
0
28 Feb 2023
Out-of-Domain Robustness via Targeted Augmentations
International Conference on Machine Learning (ICML), 2023
Irena Gao
Shiori Sagawa
Pang Wei Koh
Tatsunori Hashimoto
Abigail Z. Jacobs
OODD
OOD
217
29
0
23 Feb 2023
1
2
Next