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WILDS: A Benchmark of in-the-Wild Distribution Shifts

WILDS: A Benchmark of in-the-Wild Distribution Shifts

14 December 2020
Pang Wei Koh
Shiori Sagawa
Henrik Marklund
Sang Michael Xie
Marvin Zhang
Akshay Balsubramani
Weihua Hu
Michihiro Yasunaga
Richard Lanas Phillips
Irena Gao
Tony Lee
Etiene David
Ian Stavness
Wei Guo
Berton A. Earnshaw
I. Haque
Sara Beery
J. Leskovec
A. Kundaje
Emma Pierson
Sergey Levine
Chelsea Finn
Percy Liang
    OOD
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Papers citing "WILDS: A Benchmark of in-the-Wild Distribution Shifts"

50 / 942 papers shown
Title
Improving Out-of-Domain Robustness with Targeted Augmentation in Frequency and Pixel Spaces
Improving Out-of-Domain Robustness with Targeted Augmentation in Frequency and Pixel Spaces
Ruoqi Wang
Haitao Wang
Shaojie Guo
Qiong Luo
OOD
13
0
0
18 May 2025
Unsupervised Detection of Distribution Shift in Inverse Problems using Diffusion Models
Unsupervised Detection of Distribution Shift in Inverse Problems using Diffusion Models
Shirin Shoushtari
Edward P. Chandler
Yuanhao Wang
M. Salman Asif
Ulugbek S. Kamilov
DiffM
12
0
0
16 May 2025
Contrastive Normalizing Flows for Uncertainty-Aware Parameter Estimation
Contrastive Normalizing Flows for Uncertainty-Aware Parameter Estimation
Ibrahim Elsharkawy
Yonatan Kahn
18
0
0
13 May 2025
Fine-Grained Bias Exploration and Mitigation for Group-Robust Classification
Fine-Grained Bias Exploration and Mitigation for Group-Robust Classification
Miaoyun Zhao
Qiang Zhang
C. Li
31
0
0
11 May 2025
Wasserstein Distances Made Explainable: Insights into Dataset Shifts and Transport Phenomena
Wasserstein Distances Made Explainable: Insights into Dataset Shifts and Transport Phenomena
Philip Naumann
Jacob R. Kauffmann
G. Montavon
29
0
0
09 May 2025
Engineering Risk-Aware, Security-by-Design Frameworks for Assurance of Large-Scale Autonomous AI Models
Engineering Risk-Aware, Security-by-Design Frameworks for Assurance of Large-Scale Autonomous AI Models
Krti Tallam
31
0
0
09 May 2025
Position: Epistemic Artificial Intelligence is Essential for Machine Learning Models to Know When They Do Not Know
Position: Epistemic Artificial Intelligence is Essential for Machine Learning Models to Know When They Do Not Know
Shireen Kudukkil Manchingal
Fabio Cuzzolin
56
0
0
08 May 2025
SEVA: Leveraging Single-Step Ensemble of Vicinal Augmentations for Test-Time Adaptation
SEVA: Leveraging Single-Step Ensemble of Vicinal Augmentations for Test-Time Adaptation
Zixuan Hu
Yichun Hu
Ling-yu Duan
TTA
56
0
0
07 May 2025
Towards Application-Specific Evaluation of Vision Models: Case Studies in Ecology and Biology
Towards Application-Specific Evaluation of Vision Models: Case Studies in Ecology and Biology
A. H. H. Chan
Otto Brookes
Urs Waldmann
Hemal Naik
I. Couzin
...
Lukas Boesch
M. Arandjelovic
H. Kühl
T. Burghardt
Fumihiro Kano
164
0
0
05 May 2025
Representation Learning Preserving Ignorability and Covariate Matching for Treatment Effects
Representation Learning Preserving Ignorability and Covariate Matching for Treatment Effects
Praharsh Nanavati
Ranjitha Prasad
Karthikeyan Shanmugam
OOD
CML
66
0
0
29 Apr 2025
Improvements of Dark Experience Replay and Reservoir Sampling towards Better Balance between Consolidation and Plasticity
Improvements of Dark Experience Replay and Reservoir Sampling towards Better Balance between Consolidation and Plasticity
Taisuke Kobayashi
CLL
41
0
0
29 Apr 2025
Fast and Robust: Task Sampling with Posterior and Diversity Synergies for Adaptive Decision-Makers in Randomized Environments
Fast and Robust: Task Sampling with Posterior and Diversity Synergies for Adaptive Decision-Makers in Randomized Environments
Yun Qu
Luu Anh Tuan
Yixiu Mao
Yiqin Lv
Xiangyang Ji
TTA
90
0
0
27 Apr 2025
Multi-Resolution Pathology-Language Pre-training Model with Text-Guided Visual Representation
Multi-Resolution Pathology-Language Pre-training Model with Text-Guided Visual Representation
Shahad Albastaki
Anabia Sohail
I. I. Ganapathi
B. Alawode
Asim Khan
Sajid Javed
Naoufel Werghi
Mohammed Bennamoun
Arif Mahmood
66
0
0
26 Apr 2025
Class-Conditional Distribution Balancing for Group Robust Classification
Class-Conditional Distribution Balancing for Group Robust Classification
Miaoyun Zhao
Qiang Zhang
C. Li
70
1
0
24 Apr 2025
DataS^3: Dataset Subset Selection for Specialization
DataS^3: Dataset Subset Selection for Specialization
Neha Hulkund
Alaa Maalouf
Levi Cai
Daniel Yang
Tsun-Hsuan Wang
...
Ken Goldberg
Hannah Kerner
Irene Chen
Yogesh A. Girdhar
Sara Beery
30
0
0
22 Apr 2025
COUNTS: Benchmarking Object Detectors and Multimodal Large Language Models under Distribution Shifts
COUNTS: Benchmarking Object Detectors and Multimodal Large Language Models under Distribution Shifts
Jiansheng Li
Xingxuan Zhang
Hao Zou
Yige Guo
Renzhe Xu
Yilong Liu
Chuzhao Zhu
Yue He
Peng Cui
VLM
42
0
0
14 Apr 2025
Bayesian Cross-Modal Alignment Learning for Few-Shot Out-of-Distribution Generalization
Bayesian Cross-Modal Alignment Learning for Few-Shot Out-of-Distribution Generalization
Lin Zhu
Yifeng Yang
Zichao Nie
Yuan Gao
VLM
30
0
0
13 Apr 2025
CAShift: Benchmarking Log-Based Cloud Attack Detection under Normality Shift
CAShift: Benchmarking Log-Based Cloud Attack Detection under Normality Shift
Jiongchi Yu
Xiaofei Xie
Q. Hu
Bowen Zhang
Ziming Zhao
Yun Lin
Lei Ma
Ruitao Feng
Frank Liau
48
0
0
12 Apr 2025
Efficient Mixture of Geographical Species for On Device Wildlife Monitoring
Efficient Mixture of Geographical Species for On Device Wildlife Monitoring
Emmanuel Azuh Mensah
Joban Mand
Yueheng Ou
Min Jang
Kurtis Heimerl
41
0
0
11 Apr 2025
Self-Bootstrapping for Versatile Test-Time Adaptation
Self-Bootstrapping for Versatile Test-Time Adaptation
Shuaicheng Niu
Guohao Chen
P. Zhao
Tianyi Wang
Pengcheng Wu
Zhiqi Shen
ViT
TTA
62
0
0
10 Apr 2025
SPACE: SPike-Aware Consistency Enhancement for Test-Time Adaptation in Spiking Neural Networks
SPACE: SPike-Aware Consistency Enhancement for Test-Time Adaptation in Spiking Neural Networks
Xinyu Luo
Kecheng Chen
P. Sun
Chris Xing Tian
Arindam Basu
Haoliang Li
TTA
78
0
0
03 Apr 2025
Multivariate Temporal Regression at Scale: A Three-Pillar Framework Combining ML, XAI, and NLP
Multivariate Temporal Regression at Scale: A Three-Pillar Framework Combining ML, XAI, and NLP
Jiztom Kavalakkatt Francis
Matthew J. Darr
32
0
0
02 Apr 2025
Simple yet Effective Node Property Prediction on Edge Streams under Distribution Shifts
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Jongha Lee
Taehyung Kwon
Heechan Moon
Kijung Shin
AI4TS
46
0
0
01 Apr 2025
DGSAM: Domain Generalization via Individual Sharpness-Aware Minimization
DGSAM: Domain Generalization via Individual Sharpness-Aware Minimization
Youngjun Song
Youngsik Hwang
Jonghun Lee
Heechang Lee
Dong-Young Lim
AAML
49
0
0
30 Mar 2025
Robustness quantification: a new method for assessing the reliability of the predictions of a classifier
Robustness quantification: a new method for assessing the reliability of the predictions of a classifier
Adrián Detavernier
Jasper De Bock
UQCV
OOD
61
0
0
28 Mar 2025
Benchmarking Object Detectors under Real-World Distribution Shifts in Satellite Imagery
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Sara Al-Emadi
Yin Yang
Ferda Ofli
39
0
0
24 Mar 2025
Balanced Direction from Multifarious Choices: Arithmetic Meta-Learning for Domain Generalization
Balanced Direction from Multifarious Choices: Arithmetic Meta-Learning for Domain Generalization
Xiran Wang
Jian Zhang
Lei Qi
Yinghuan Shi
61
0
0
23 Mar 2025
Rethinking Robustness in Machine Learning: A Posterior Agreement Approach
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João B. S. Carvalho
Alessandro Torcinovich
Victor Jimenez Rodriguez
Antonio Emanuele Cinà
Carlos Cotrini
Lea Schönherr
J. M. Buhmann
OOD
68
0
0
20 Mar 2025
LeanTTA: A Backpropagation-Free and Stateless Approach to Quantized Test-Time Adaptation on Edge Devices
LeanTTA: A Backpropagation-Free and Stateless Approach to Quantized Test-Time Adaptation on Edge Devices
Cynthia Dong
Hong Jia
Young D. Kwon
Georgios Rizos
Cecilia Mascolo
MQ
68
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0
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In Shift and In Variance: Assessing the Robustness of HAR Deep Learning Models against Variability
Azhar Ali Khaked
Nobuyuki Oishi
Daniel Roggen
Paula Lago
47
0
0
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Divide and Conquer Self-Supervised Learning for High-Content Imaging
Lucas Farndale
Paul Henderson
Edward W Roberts
Ke Yuan
SSL
63
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0
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Group-robust Sample Reweighting for Subpopulation Shifts via Influence Functions
Rui Qiao
Zhaoxuan Wu
Jingtan Wang
Pang Wei Koh
Bryan Kian Hsiang Low
OOD
53
2
0
10 Mar 2025
Learning Decision Trees as Amortized Structure Inference
Mohammed Mahfoud
Ghait Boukachab
Michał Koziarski
A. Garcia
Stefan Bauer
Yoshua Bengio
Nikolay Malkin
BDL
53
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0
10 Mar 2025
Elliptic Loss Regularization
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Haoming Yang
Yuting Ng
Vahid Tarokh
76
1
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A generalized approach to label shift: the Conditional Probability Shift Model
Paweł Teisseyre
J. Mielniczuk
49
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Robustness to Geographic Distribution Shift using Location Encoders
Ruth Crasto
OOD
81
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A Guide to Failure in Machine Learning: Reliability and Robustness from Foundations to Practice
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OOD
FaML
68
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The PanAf-FGBG Dataset: Understanding the Impact of Backgrounds in Wildlife Behaviour Recognition
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Majid Mirmehdi
Colleen Stephens
Paula Dieguez
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H. Kühl
T. Burghardt
48
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Robust Gymnasium: A Unified Modular Benchmark for Robust Reinforcement Learning
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36
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Kandinsky Conformal Prediction: Beyond Class- and Covariate-Conditional Coverage
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DivIL: Unveiling and Addressing Over-Invariance for Out-of- Distribution Generalization
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Zhixiong Zhang
Qiguang Chen
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60
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Likelihood-Ratio Regularized Quantile Regression: Adapting Conformal Prediction to High-Dimensional Covariate Shifts
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Shayan Kiyani
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Yan Sun
Hamed Hassani
73
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0
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101
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43
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Sebra: Debiasing Through Self-Guided Bias Ranking
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Abhra Chaudhuri
Ajay Jaiswal
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137
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Towards Understanding Extrapolation: a Causal Lens
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