ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2105.05612
  4. Cited By
Evading the Simplicity Bias: Training a Diverse Set of Models Discovers
  Solutions with Superior OOD Generalization

Evading the Simplicity Bias: Training a Diverse Set of Models Discovers Solutions with Superior OOD Generalization

12 May 2021
Damien Teney
Ehsan Abbasnejad
Simon Lucey
A. Hengel
ArXivPDFHTML

Papers citing "Evading the Simplicity Bias: Training a Diverse Set of Models Discovers Solutions with Superior OOD Generalization"

50 / 63 papers shown
Title
Do We Always Need the Simplicity Bias? Looking for Optimal Inductive Biases in the Wild
Damien Teney
Liangze Jiang
Florin Gogianu
Ehsan Abbasnejad
112
0
0
13 Mar 2025
Sub-Sequential Physics-Informed Learning with State Space Model
Sub-Sequential Physics-Informed Learning with State Space Model
Chenhui Xu
Dancheng Liu
Yuting Hu
Jiajie Li
Ruiyang Qin
Qingxiao Zheng
Jinjun Xiong
AI4CE
PINN
96
0
0
01 Feb 2025
Test-Time Alignment via Hypothesis Reweighting
Test-Time Alignment via Hypothesis Reweighting
Yoonho Lee
Jonathan Williams
Henrik Marklund
Archit Sharma
E. Mitchell
Anikait Singh
Chelsea Finn
91
3
0
11 Dec 2024
Long-Tailed Object Detection Pre-training: Dynamic Rebalancing
  Contrastive Learning with Dual Reconstruction
Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction
Chen-Long Duan
Yong Li
Xiu-Shen Wei
Lin Zhao
34
1
0
14 Nov 2024
Impact of Label Noise on Learning Complex Features
Impact of Label Noise on Learning Complex Features
Rahul Vashisht
P. Krishna Kumar
Harsha Vardhan Govind
H. G. Ramaswamy
NoLa
26
0
0
07 Nov 2024
Scalable Ensemble Diversification for OOD Generalization and Detection
Scalable Ensemble Diversification for OOD Generalization and Detection
Alexander Rubinstein
Luca Scimeca
Damien Teney
Seong Joon Oh
BDL
OOD
351
1
0
25 Sep 2024
Model Debiasing by Learnable Data Augmentation
Model Debiasing by Learnable Data Augmentation
Pietro Morerio
R. Ragonesi
Vittorio Murino
35
0
0
09 Aug 2024
DIVE: Subgraph Disagreement for Graph Out-of-Distribution Generalization
DIVE: Subgraph Disagreement for Graph Out-of-Distribution Generalization
Xin Sun
Liang Wang
Qiang Liu
Shu Wu
Zilei Wang
Liang Wang
OOD
CML
31
5
0
08 Aug 2024
Model Guidance via Explanations Turns Image Classifiers into
  Segmentation Models
Model Guidance via Explanations Turns Image Classifiers into Segmentation Models
Xiaoyan Yu
Jannik Franzen
Wojciech Samek
Marina M.-C. Höhne
Dagmar Kainmueller
28
0
0
03 Jul 2024
How Does Distribution Matching Help Domain Generalization: An
  Information-theoretic Analysis
How Does Distribution Matching Help Domain Generalization: An Information-theoretic Analysis
Yuxin Dong
Tieliang Gong
Hong Chen
Shuangyong Song
Weizhan Zhang
Chen Li
OOD
37
0
0
14 Jun 2024
Sharpness-Aware Minimization Enhances Feature Quality via Balanced
  Learning
Sharpness-Aware Minimization Enhances Feature Quality via Balanced Learning
Jacob Mitchell Springer
Vaishnavh Nagarajan
Aditi Raghunathan
37
5
0
30 May 2024
Siamese Vision Transformers are Scalable Audio-visual Learners
Siamese Vision Transformers are Scalable Audio-visual Learners
Yan-Bo Lin
Gedas Bertasius
37
5
0
28 Mar 2024
Complexity Matters: Dynamics of Feature Learning in the Presence of
  Spurious Correlations
Complexity Matters: Dynamics of Feature Learning in the Presence of Spurious Correlations
GuanWen Qiu
Da Kuang
Surbhi Goel
25
8
0
05 Mar 2024
Neural Redshift: Random Networks are not Random Functions
Neural Redshift: Random Networks are not Random Functions
Damien Teney
A. Nicolicioiu
Valentin Hartmann
Ehsan Abbasnejad
89
18
0
04 Mar 2024
Clarify: Improving Model Robustness With Natural Language Corrections
Clarify: Improving Model Robustness With Natural Language Corrections
Yoonho Lee
Michelle S. Lam
Helena Vasconcelos
Michael S. Bernstein
Chelsea Finn
23
6
0
06 Feb 2024
Medical Image Debiasing by Learning Adaptive Agreement from a Biased
  Council
Medical Image Debiasing by Learning Adaptive Agreement from a Biased Council
Luyang Luo
Xin Huang
Minghao Wang
Zhuoyue Wan
Hao Chen
15
2
0
22 Jan 2024
Prompt-driven Latent Domain Generalization for Medical Image
  Classification
Prompt-driven Latent Domain Generalization for Medical Image Classification
Siyuan Yan
Chi Liu
Zhen Yu
Lie Ju
Dwarikanath Mahapatra
B. Betz‐Stablein
Victoria Mar
Monika Janda
Peter Soyer
Zongyuan Ge
OOD
VLM
MedIm
35
6
0
05 Jan 2024
Unraveling the Key Components of OOD Generalization via Diversification
Unraveling the Key Components of OOD Generalization via Diversification
Harold Benoit
Liangze Jiang
Andrei Atanov
Ouguzhan Fatih Kar
Mattia Rigotti
Amir Zamir
CML
22
2
0
26 Dec 2023
DoubleAUG: Single-domain Generalized Object Detector in Urban via Color
  Perturbation and Dual-style Memory
DoubleAUG: Single-domain Generalized Object Detector in Urban via Color Perturbation and Dual-style Memory
Lei Qi
Peng Dong
Tan Xiong
Hui Xue
Xin Geng
26
4
0
22 Nov 2023
Attribute-Aware Deep Hashing with Self-Consistency for Large-Scale
  Fine-Grained Image Retrieval
Attribute-Aware Deep Hashing with Self-Consistency for Large-Scale Fine-Grained Image Retrieval
Xiu-Shen Wei
Yang Shen
Xuhao Sun
Peng Wang
Yuxin Peng
22
10
0
21 Nov 2023
MADG: Margin-based Adversarial Learning for Domain Generalization
MADG: Margin-based Adversarial Learning for Domain Generalization
Aveen Dayal
B. VimalK.
Linga Reddy Cenkeramaddi
C. K. Mohan
Abhinav Kumar
Vineeth N. Balasubramanian
OOD
AAML
24
62
0
14 Nov 2023
Using Early Readouts to Mediate Featural Bias in Distillation
Using Early Readouts to Mediate Featural Bias in Distillation
Rishabh Tiwari
D. Sivasubramanian
Anmol Reddy Mekala
Ganesh Ramakrishnan
Pradeep Shenoy
22
5
0
28 Oct 2023
On the Foundations of Shortcut Learning
On the Foundations of Shortcut Learning
Katherine Hermann
Hossein Mobahi
Thomas Fel
M. C. Mozer
VLM
30
25
0
24 Oct 2023
Mitigating Simplicity Bias in Deep Learning for Improved OOD
  Generalization and Robustness
Mitigating Simplicity Bias in Deep Learning for Improved OOD Generalization and Robustness
Bhavya Vasudeva
Kameron Shahabi
Vatsal Sharan
22
2
0
09 Oct 2023
Leveraging Diffusion Disentangled Representations to Mitigate Shortcuts
  in Underspecified Visual Tasks
Leveraging Diffusion Disentangled Representations to Mitigate Shortcuts in Underspecified Visual Tasks
Luca Scimeca
Alexander Rubinstein
A. Nicolicioiu
Damien Teney
Yoshua Bengio
DiffM
24
2
0
03 Oct 2023
Spurious Feature Diversification Improves Out-of-distribution
  Generalization
Spurious Feature Diversification Improves Out-of-distribution Generalization
Yong Lin
Lu Tan
Yifan Hao
Honam Wong
Hanze Dong
Weizhong Zhang
Yujiu Yang
Tong Zhang
OODD
16
24
0
29 Sep 2023
CoinRun: Solving Goal Misgeneralisation
CoinRun: Solving Goal Misgeneralisation
Stuart Armstrong
Alexandre Maranhao
Oliver Daniels-Koch
Ioannis Gkioulekas
Rebecca Gormann
LRM
27
0
0
28 Sep 2023
Learning Diverse Features in Vision Transformers for Improved
  Generalization
Learning Diverse Features in Vision Transformers for Improved Generalization
A. Nicolicioiu
Andrei Liviu Nicolicioiu
B. Alexe
Damien Teney
27
3
0
30 Aug 2023
Cross Contrasting Feature Perturbation for Domain Generalization
Cross Contrasting Feature Perturbation for Domain Generalization
Chenming Li
Daoan Zhang
Wen-Fong Huang
Jiang Zhang
OOD
16
17
0
24 Jul 2023
Confidence-Based Model Selection: When to Take Shortcuts for
  Subpopulation Shifts
Confidence-Based Model Selection: When to Take Shortcuts for Subpopulation Shifts
Annie S. Chen
Yoonho Lee
Amrith Rajagopal Setlur
Sergey Levine
Chelsea Finn
OOD
14
5
0
19 Jun 2023
How to Construct Perfect and Worse-than-Coin-Flip Spoofing
  Countermeasures: A Word of Warning on Shortcut Learning
How to Construct Perfect and Worse-than-Coin-Flip Spoofing Countermeasures: A Word of Warning on Shortcut Learning
Hye-jin Shim
Rosa González Hautamäki
Md. Sahidullah
Tomi Kinnunen
AAML
8
5
0
31 May 2023
Identifying Spurious Biases Early in Training through the Lens of
  Simplicity Bias
Identifying Spurious Biases Early in Training through the Lens of Simplicity Bias
Yu Yang
Eric Gan
Gintare Karolina Dziugaite
Baharan Mirzasoleiman
16
25
0
30 May 2023
Few-shot Adaptation to Distribution Shifts By Mixing Source and Target
  Embeddings
Few-shot Adaptation to Distribution Shifts By Mixing Source and Target Embeddings
Yihao Xue
Ali Payani
Yu Yang
Baharan Mirzasoleiman
VLM
24
4
0
23 May 2023
Echoes: Unsupervised Debiasing via Pseudo-bias Labeling in an Echo
  Chamber
Echoes: Unsupervised Debiasing via Pseudo-bias Labeling in an Echo Chamber
Rui Hu
Yahan Tu
Jitao Sang
24
2
0
06 May 2023
A Closer Look at Model Adaptation using Feature Distortion and
  Simplicity Bias
A Closer Look at Model Adaptation using Feature Distortion and Simplicity Bias
Puja Trivedi
Danai Koutra
Jayaraman J. Thiagarajan
AAML
27
17
0
23 Mar 2023
Spawrious: A Benchmark for Fine Control of Spurious Correlation Biases
Spawrious: A Benchmark for Fine Control of Spurious Correlation Biases
Aengus Lynch
G. Dovonon
Jean Kaddour
Ricardo M. A. Silva
184
30
0
09 Mar 2023
Project and Probe: Sample-Efficient Domain Adaptation by Interpolating
  Orthogonal Features
Project and Probe: Sample-Efficient Domain Adaptation by Interpolating Orthogonal Features
Annie S. Chen
Yoonho Lee
Amrith Rajagopal Setlur
Sergey Levine
Chelsea Finn
VLM
16
9
0
10 Feb 2023
Delving Deep into Simplicity Bias for Long-Tailed Image Recognition
Delving Deep into Simplicity Bias for Long-Tailed Image Recognition
Xiu-Shen Wei
Xuhao Sun
Yang Shen
Anqi Xu
Peng Wang
Faen Zhang
23
1
0
07 Feb 2023
Improving Domain Generalization with Domain Relations
Improving Domain Generalization with Domain Relations
Huaxiu Yao
Xinyu Yang
Xinyi Pan
Shengchao Liu
Pang Wei Koh
Chelsea Finn
OOD
AI4CE
37
8
0
06 Feb 2023
Pathologies of Predictive Diversity in Deep Ensembles
Pathologies of Predictive Diversity in Deep Ensembles
Taiga Abe
E. Kelly Buchanan
Geoff Pleiss
John P. Cunningham
UQCV
17
13
0
01 Feb 2023
Simplicity Bias in 1-Hidden Layer Neural Networks
Simplicity Bias in 1-Hidden Layer Neural Networks
Depen Morwani
Jatin Batra
Prateek Jain
Praneeth Netrapalli
14
17
0
01 Feb 2023
Overcoming Simplicity Bias in Deep Networks using a Feature Sieve
Overcoming Simplicity Bias in Deep Networks using a Feature Sieve
Rishabh Tiwari
Pradeep Shenoy
35
17
0
30 Jan 2023
Learning useful representations for shifting tasks and distributions
Learning useful representations for shifting tasks and distributions
Jianyu Zhang
Léon Bottou
OOD
27
13
0
14 Dec 2022
Denoising after Entropy-based Debiasing A Robust Training Method for
  Dataset Bias with Noisy Labels
Denoising after Entropy-based Debiasing A Robust Training Method for Dataset Bias with Noisy Labels
Sumyeong Ahn
Se-Young Yun
NoLa
19
2
0
01 Dec 2022
SelecMix: Debiased Learning by Contradicting-pair Sampling
SelecMix: Debiased Learning by Contradicting-pair Sampling
Inwoo Hwang
Sangjun Lee
Yunhyeok Kwak
Seong Joon Oh
Damien Teney
Jin-Hwa Kim
Byoung-Tak Zhang
OOD
321
21
0
04 Nov 2022
On Feature Learning in the Presence of Spurious Correlations
On Feature Learning in the Presence of Spurious Correlations
Pavel Izmailov
Polina Kirichenko
Nate Gruver
A. Wilson
21
116
0
20 Oct 2022
Learning an Invertible Output Mapping Can Mitigate Simplicity Bias in
  Neural Networks
Learning an Invertible Output Mapping Can Mitigate Simplicity Bias in Neural Networks
Sravanti Addepalli
Anshul Nasery
R. Venkatesh Babu
Praneeth Netrapalli
Prateek Jain
AAML
18
3
0
04 Oct 2022
ID and OOD Performance Are Sometimes Inversely Correlated on Real-world
  Datasets
ID and OOD Performance Are Sometimes Inversely Correlated on Real-world Datasets
Damien Teney
Yong Lin
Seong Joon Oh
Ehsan Abbasnejad
OOD
360
47
0
01 Sep 2022
Predicting is not Understanding: Recognizing and Addressing
  Underspecification in Machine Learning
Predicting is not Understanding: Recognizing and Addressing Underspecification in Machine Learning
Damien Teney
Maxime Peyrard
Ehsan Abbasnejad
17
29
0
06 Jul 2022
How Robust is Unsupervised Representation Learning to Distribution
  Shift?
How Robust is Unsupervised Representation Learning to Distribution Shift?
Yuge Shi
Imant Daunhawer
Julia E. Vogt
Philip H. S. Torr
Amartya Sanyal
OOD
22
25
0
17 Jun 2022
12
Next