Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing | Paper Citation Record

Observation 9973f16f-0dcb-482b-b1e2-545eb05ca505 · outbound

This paper cites Invariant Risk Minimization.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing Invariant Risk Minimization

Reference 1

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Observation 7f89de21-d9d9-4be4-97f1-34db4ad6cb9f · outbound

This paper cites The Pitfalls of Memorization: When Memorization Hurts Generalization.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing The Pitfalls of Memorization: When Memorization Hurts Generalization

Reference 2

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Observation f83f5f87-af07-4d9b-881d-1d9a094ad54f · outbound

This paper cites How spurious features are memorized: Precise analysis for random and ntk features.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing How spurious features are memorized: Precise analysis for random and ntk features

Reference 3

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This paper cites Environment inference for invariant learning.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing Environment inference for invariant learning

Reference 4

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This paper cites Robust learning with pro- gressive data expansion against spurious correlation.Advances in neural information processing systems, 36:1390–1402, 2023.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing Robust learning with pro- gressive data expansion against spurious correlation.Advances in neural information processing systems, 36:1390–1402, 2023

Reference 5

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This paper cites The impact of coreset selection on spurious correlations and group robustness.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing The impact of coreset selection on spurious correlations and group robustness

Reference 6

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Observation e51a8560-04d7-4ecd-b1aa-e2f84aaf2c2a · outbound

This paper cites Optimal shrinkage of eigenvalues in the spiked covariance model.Annals of statistics, 46(4):1742, 2018.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing Optimal shrinkage of eigenvalues in the spiked covariance model.Annals of statistics, 46(4):1742, 2018

Reference 7

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Observation 7d4f40b9-049b-401d-bc13-d4f38d3361c3 · outbound

This paper cites Does learning require memorization? a short tale about a long tail.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing Does learning require memorization? a short tale about a long tail

Reference 8

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Observation 10b44b36-fd1d-4783-9049-eed7bb3d47b3 · outbound

This paper cites Neural tangent kernel: Convergence and generalization in neural networks.Advances in neural information processing systems, 31, 2018.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing Neural tangent kernel: Convergence and generalization in neural networks.Advances in neural information processing systems, 31, 2018

Reference 9

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This paper cites Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations

Reference 10

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Observation fe2b090f-6f59-4c6d-99fb-9fa30c588f86 · outbound

This paper cites Wide neural networks of any depth evolve as linear models under gradient descent.Advances in neural information processing systems, 32, 2019.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing Wide neural networks of any depth evolve as linear models under gradient descent.Advances in neural information processing systems, 32, 2019

Reference 11

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Observation 3b9b2450-ad3d-4b32-b08d-9d7e0fadeaa5 · outbound

This paper cites A whac-a-mole dilemma: Shortcuts come in multiples where mitigating one amplifies others.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing A whac-a-mole dilemma: Shortcuts come in multiples where mitigating one amplifies others

Reference 12

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This paper cites Metashift: A dataset of datasets for evaluating contextual distri- bution shifts and training conflicts.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing Metashift: A dataset of datasets for evaluating contextual distri- bution shifts and training conflicts

Reference 13

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Observation 461290c2-ea86-4f98-9e45-ee015bd46f5f · outbound

This paper cites The global k-means clustering algorithm.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing The global k-means clustering algorithm

Reference 14

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This paper cites Just train twice: Improving group robustness without training group information.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing Just train twice: Improving group robustness without training group information

Reference 15

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This paper cites Avoiding spurious correlations via logit correction.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing Avoiding spurious correlations via logit correction

Reference 16

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Observation c1e9a03f-3d0b-4b54-8302-11ca6ad56db7 · outbound

This paper cites D2 Pruning: Message Passing for Balancing Diversity and Difficulty in Data Pruning.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing D2 Pruning: Message Passing for Balancing Diversity and Difficulty in Data Pruning

Reference 17

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Observation ccf813a5-8240-4670-81a1-db520161891e · outbound

This paper cites Severing spurious correlations with data pruning.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing Severing spurious correlations with data pruning

Reference 18

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This paper cites SGD on Neural Networks Learns Functions of Increasing Complexity.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing SGD on Neural Networks Learns Functions of Increasing Complexity

Reference 19

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Observation 33f80d23-11df-487b-84dc-4ea24daf4861 · outbound

This paper cites Learning from failure: De-biasing classifier from biased classifier.Advances in Neural Information Processing Systems, 33:20673–20684, 2020.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing Learning from failure: De-biasing classifier from biased classifier.Advances in Neural Information Processing Systems, 33:20673–20684, 2020

Reference 20

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Observation 8eae3e9f-a499-4fa2-890f-bd324fd74e66 · outbound

This paper cites TRAK: Attributing Model Behavior at Scale.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing TRAK: Attributing Model Behavior at Scale

Reference 21

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Observation 77dc6e96-32f7-4388-85c6-19eaf26cc079 · outbound

This paper cites Asymptotics of sample eigenstructure for a large dimensional spiked covariance model.Statistica Sinica, pages 1617–1642, 2007.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing Asymptotics of sample eigenstructure for a large dimensional spiked covariance model.Statistica Sinica, pages 1617–1642, 2007

Reference 22

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This paper cites Deep learning on a data diet: Finding important examples early in training.Advances in neural information processing systems, 34:20596–20607, 2021.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing Deep learning on a data diet: Finding important examples early in training.Advances in neural information processing systems, 34:20596–20607, 2021

Reference 23

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This paper cites Complexity Matters: Dynamics of Feature Learning in the Presence of Spurious Correlations.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing Complexity Matters: Dynamics of Feature Learning in the Presence of Spurious Correlations

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Observation 884ca24c-6fa2-42a9-a5d7-a165c019cea4 · outbound

This paper cites Simple and fast group robustness by automatic feature reweighting.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing Simple and fast group robustness by automatic feature reweighting

Reference 25

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Observation b6c72972-a0f3-45dd-b470-6b988af3e539 · outbound

This paper cites Learning transferable visual models from natural language supervision.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing Learning transferable visual models from natural language supervision

Reference 26

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Observation 2e9cf264-5e47-416f-8ba1-754149725d64 · outbound

This paper cites Towards mem- orization estimation: Fast, formal and free.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing Towards mem- orization estimation: Fast, formal and free

Reference 27

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Observation 996adf22-4ab4-4fd6-9a6d-7e338751c715 · outbound

This paper cites Imagenet large scale visual recognition challenge.International journal of computer vision, 115(3):211–252, 2015.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing Imagenet large scale visual recognition challenge.International journal of computer vision, 115(3):211–252, 2015

Reference 28

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This paper cites Distributionally robust neural networks.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing Distributionally robust neural networks

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Observation 66d58707-a479-446d-b527-5a9e99a1254c · outbound

This paper cites Upweighting easy samples in fine-tuning mitigates forgetting.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing Upweighting easy samples in fine-tuning mitigates forgetting

Reference 31

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Observation ae4a061c-ab72-4c75-8bac-fbb7dcc90374 · outbound

This paper cites The pitfalls of simplicity bias in neural networks.Advances in Neural Information Processing Systems, 33:9573–9585, 2020.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing The pitfalls of simplicity bias in neural networks.Advances in Neural Information Processing Systems, 33:9573–9585, 2020

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This paper cites No subclass left behind: Fine-grained robustness in coarse-grained classification problems.Advances in Neural Information Processing Systems, 33:19339–19352, 2020.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing No subclass left behind: Fine-grained robustness in coarse-grained classification problems.Advances in Neural Information Processing Systems, 33:19339–19352, 2020

Reference 33

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This paper cites Beyond neural scaling laws: beating power law scaling via data pruning.Advances in Neural Informa- tion Processing Systems, 35:19523–19536, 2022.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing Beyond neural scaling laws: beating power law scaling via data pruning.Advances in Neural Informa- tion Processing Systems, 35:19523–19536, 2022

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This paper cites Group robust classification without any group information.Advances in Neural Information Processing Systems, 36:56553–56575, 2023.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing Group robust classification without any group information.Advances in Neural Information Processing Systems, 36:56553–56575, 2023

Reference 35

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This paper cites Deep learning generalizes because the parameter-function map is biased towards simple functions.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing Deep learning generalizes because the parameter-function map is biased towards simple functions

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Observation a9360073-5fe3-4c1a-8b8a-e9dffa20c707 · outbound

This paper cites Drop: Distributionally robust data pruning.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing Drop: Distributionally robust data pruning

Reference 37

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This paper cites The caltech-ucsd birds-200-2011 dataset.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing The caltech-ucsd birds-200-2011 dataset

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This paper cites On the effect of key factors in spurious correlation: A theoretical perspective.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing On the effect of key factors in spurious correlation: A theoretical perspective

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This paper cites Nonlinear spiked covariance matrices and signal propagation in deep neural networks.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing Nonlinear spiked covariance matrices and signal propagation in deep neural networks

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This paper cites Identifying spurious biases early in training through the lens of simplicity bias.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing Identifying spurious biases early in training through the lens of simplicity bias

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This paper cites Correct-N-Contrast: A Contrastive Approach for Improving Robustness to Spurious Correlations.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing Correct-N-Contrast: A Contrastive Approach for Improving Robustness to Spurious Correlations

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Observation 26e4d7b8-b8c2-4d76-b731-0b1438e26b6c · outbound

This paper cites Generalized cross entropy loss for training deep neural net- works with noisy labels.Advances in neural information processing systems, 31, 2018.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing Generalized cross entropy loss for training deep neural net- works with noisy labels.Advances in neural information processing systems, 31, 2018

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This paper cites Coverage-centric coreset selection for high pruning rates.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing Coverage-centric coreset selection for high pruning rates

Reference 45

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Observation 62a5200b-c84e-4bc1-9b3c-a01adc622933 · outbound

This paper cites Places: An Image Database for Deep Scene Understanding.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing Places: An Image Database for Deep Scene Understanding

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Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing Unresolved cited work

Reference 47

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Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing Unresolved cited work

Reference 48

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Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing Unresolved cited work

Reference 49

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Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing Unresolved cited work

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This paper cites 21 Proof.By Assumption 1, the initial expected logit is ¯h0(xj) = 0, so the initial expected margin is ¯m0(xj) = 0.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing 21 Proof.By Assumption 1, the initial expected logit is ¯h0(xj) = 0, so the initial expected margin is ¯m0(xj) = 0

Reference 51

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This paper cites The initial velocity isR c +R s = βc 2 + βs(2α−1) 2 >0.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing The initial velocity isR c +R s = βc 2 + βs(2α−1) 2 >0

Reference 52

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This paper cites hard” (lowβ) and “easy.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing hard” (lowβ) and “easy

Reference 53

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This paper cites High-Dimensional Statistics A Non-Asymptotic Viewpoint.

Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing High-Dimensional Statistics A Non-Asymptotic Viewpoint

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