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. 2005.04345
  4. Cited By
An Investigation of Why Overparameterization Exacerbates Spurious
  Correlations

An Investigation of Why Overparameterization Exacerbates Spurious Correlations

9 May 2020
Shiori Sagawa
Aditi Raghunathan
Pang Wei Koh
Percy Liang
ArXivPDFHTML

Papers citing "An Investigation of Why Overparameterization Exacerbates Spurious Correlations"

29 / 79 papers shown
Title
Towards out of distribution generalization for problems in mechanics
Towards out of distribution generalization for problems in mechanics
Lingxiao Yuan
Harold S. Park
Emma Lejeune
OOD
AI4CE
33
17
0
29 Jun 2022
Marrying Fairness and Explainability in Supervised Learning
Marrying Fairness and Explainability in Supervised Learning
Przemyslaw A. Grabowicz
Nicholas Perello
Aarshee Mishra
FaML
38
43
0
06 Apr 2022
OccamNets: Mitigating Dataset Bias by Favoring Simpler Hypotheses
OccamNets: Mitigating Dataset Bias by Favoring Simpler Hypotheses
Robik Shrestha
Kushal Kafle
Christopher Kanan
CML
33
13
0
05 Apr 2022
Evaluating Distributional Distortion in Neural Language Modeling
Evaluating Distributional Distortion in Neural Language Modeling
Benjamin LeBrun
Alessandro Sordoni
Timothy J. O'Donnell
22
22
0
24 Mar 2022
Understanding Rare Spurious Correlations in Neural Networks
Understanding Rare Spurious Correlations in Neural Networks
Yao-Yuan Yang
Chi-Ning Chou
Kamalika Chaudhuri
AAML
16
25
0
10 Feb 2022
Aligning Eyes between Humans and Deep Neural Network through Interactive
  Attention Alignment
Aligning Eyes between Humans and Deep Neural Network through Interactive Attention Alignment
Yuyang Gao
Tong Sun
Liang Zhao
Sungsoo Ray Hong
HAI
21
37
0
06 Feb 2022
Datamodels: Predicting Predictions from Training Data
Datamodels: Predicting Predictions from Training Data
Andrew Ilyas
Sung Min Park
Logan Engstrom
Guillaume Leclerc
A. Madry
TDI
38
130
0
01 Feb 2022
Vision Checklist: Towards Testable Error Analysis of Image Models to
  Help System Designers Interrogate Model Capabilities
Vision Checklist: Towards Testable Error Analysis of Image Models to Help System Designers Interrogate Model Capabilities
Xin Du
Bénédicte Legastelois
B. Ganesh
A. Rajan
Hana Chockler
Vaishak Belle
Stuart Anderson
S. Ramamoorthy
AAML
21
6
0
27 Jan 2022
Towards Group Robustness in the presence of Partial Group Labels
Towards Group Robustness in the presence of Partial Group Labels
Vishnu Suresh Lokhande
Kihyuk Sohn
Jinsung Yoon
Madeleine Udell
Chen-Yu Lee
Tomas Pfister
OOD
34
11
0
10 Jan 2022
Measure and Improve Robustness in NLP Models: A Survey
Measure and Improve Robustness in NLP Models: A Survey
Xuezhi Wang
Haohan Wang
Diyi Yang
139
130
0
15 Dec 2021
The Effect of Model Size on Worst-Group Generalization
The Effect of Model Size on Worst-Group Generalization
Alan Pham
Eunice Chan
V. Srivatsa
Dhruba Ghosh
Yaoqing Yang
Yaodong Yu
Ruiqi Zhong
Joseph E. Gonzalez
Jacob Steinhardt
20
5
0
08 Dec 2021
Learning Invariant Representations with Missing Data
Learning Invariant Representations with Missing Data
Mark Goldstein
J. Jacobsen
O. Chau
A. Saporta
A. Puli
Rajesh Ranganath
Andrew C. Miller
OOD
17
5
0
01 Dec 2021
Towards Robust and Adaptive Motion Forecasting: A Causal Representation
  Perspective
Towards Robust and Adaptive Motion Forecasting: A Causal Representation Perspective
Yuejiang Liu
Riccardo Cadei
Jonas Schweizer
Sherwin Bahmani
Alexandre Alahi
OOD
TTA
35
51
0
29 Nov 2021
Simple data balancing achieves competitive worst-group-accuracy
Simple data balancing achieves competitive worst-group-accuracy
Badr Youbi Idrissi
Martín Arjovsky
Mohammad Pezeshki
David Lopez-Paz
33
173
0
27 Oct 2021
Identifying and Mitigating Spurious Correlations for Improving
  Robustness in NLP Models
Identifying and Mitigating Spurious Correlations for Improving Robustness in NLP Models
Tianlu Wang
Rohit Sridhar
Diyi Yang
Xuezhi Wang
AAML
120
72
0
14 Oct 2021
Focus on the Common Good: Group Distributional Robustness Follows
Focus on the Common Good: Group Distributional Robustness Follows
Vihari Piratla
Praneeth Netrapalli
Sunita Sarawagi
OOD
26
25
0
06 Oct 2021
Enhancing Model Robustness and Fairness with Causality: A Regularization
  Approach
Enhancing Model Robustness and Fairness with Causality: A Regularization Approach
Zhao Wang
Kai Shu
A. Culotta
OOD
21
14
0
03 Oct 2021
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
Towards Out-Of-Distribution Generalization: A Survey
Towards Out-Of-Distribution Generalization: A Survey
Jiashuo Liu
Zheyan Shen
Yue He
Xingxuan Zhang
Renzhe Xu
Han Yu
Peng Cui
CML
OOD
55
516
0
31 Aug 2021
Unsupervised Learning of Debiased Representations with Pseudo-Attributes
Unsupervised Learning of Debiased Representations with Pseudo-Attributes
Seonguk Seo
Joon-Young Lee
Bohyung Han
FaML
68
48
0
06 Aug 2021
Learning Stable Classifiers by Transferring Unstable Features
Learning Stable Classifiers by Transferring Unstable Features
Yujia Bao
Shiyu Chang
Regina Barzilay
OOD
24
8
0
15 Jun 2021
Examining and Combating Spurious Features under Distribution Shift
Examining and Combating Spurious Features under Distribution Shift
Chunting Zhou
Xuezhe Ma
Paul Michel
Graham Neubig
OOD
27
66
0
14 Jun 2021
DORO: Distributional and Outlier Robust Optimization
DORO: Distributional and Outlier Robust Optimization
Runtian Zhai
Chen Dan
J. Zico Kolter
Pradeep Ravikumar
33
58
0
11 Jun 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
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
Damien Teney
Ehsan Abbasnejad
Simon Lucey
A. Hengel
23
86
0
12 May 2021
On complementing end-to-end human behavior predictors with planning
On complementing end-to-end human behavior predictors with planning
Liting Sun
Xiaogang Jia
Anca Dragan
29
17
0
09 Mar 2021
Label-Imbalanced and Group-Sensitive Classification under
  Overparameterization
Label-Imbalanced and Group-Sensitive Classification under Overparameterization
Ganesh Ramachandra Kini
Orestis Paraskevas
Samet Oymak
Christos Thrampoulidis
27
93
0
02 Mar 2021
Stable Adversarial Learning under Distributional Shifts
Stable Adversarial Learning under Distributional Shifts
Jiashuo Liu
Zheyan Shen
Peng Cui
Linjun Zhou
Kun Kuang
B. Li
Yishi Lin
OOD
19
30
0
08 Jun 2020
Adversarial Filters of Dataset Biases
Adversarial Filters of Dataset Biases
Ronan Le Bras
Swabha Swayamdipta
Chandra Bhagavatula
Rowan Zellers
Matthew E. Peters
Ashish Sabharwal
Yejin Choi
34
220
0
10 Feb 2020
Previous
12