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Paper Citation Record · LEDGER

Benign Overfitting in Out-of-Distribution Generalization of Linear Models

As of 13 August 2026, this Paper Citation Record lists 86 of 86 outbound references and 0 inbound Pith citation observations for arXiv:2412.14474.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2412.14474 v1

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measured 86 of 86 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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Source: cited_works

Reference resolution

86 of 86 outbound references displayed

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External citation measurements

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Outbound references

Observation 9c9fba9b-4691-4d15-951c-e0d9ed04c27a · outbound

This paper cites write newline.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models write newline

Reference 1

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Observation dbe5c401-9d38-4e59-94c4-24e1ed63a8a6 · outbound

This paper cites Importance sampling: Intrinsic dimension and computational cost.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Importance sampling: Intrinsic dimension and computational cost

Reference 2

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This paper cites On robustness of principal component regression.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models On robustness of principal component regression

Reference 3

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This paper cites Determining the number of factors in approximate factor models.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Determining the number of factors in approximate factor models

Reference 5

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This paper cites Prediction by supervised principal components.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Prediction by supervised principal components

Reference 6

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This paper cites Benign overfitting in linear regression.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Benign overfitting in linear regression

Reference 7

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Benign Overfitting in Out-of-Distribution Generalization of Linear Models Deep learning: a statistical viewpoint

Reference 8

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Benign Overfitting in Out-of-Distribution Generalization of Linear Models Laplacian eigenmaps for dimensionality reduction and data representation

Reference 9

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This paper cites Two models of double descent for weak features.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Two models of double descent for weak features

Reference 10

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This paper cites Analysis of representations for domain adaptation.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Analysis of representations for domain adaptation

Reference 11

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This paper cites A new look at an old problem: A universal learning approach to linear regression.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models A new look at an old problem: A universal learning approach to linear regression

Reference 12

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Benign Overfitting in Out-of-Distribution Generalization of Linear Models Project cost estimation using principal component regression

Reference 13

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This paper cites High-dimensional kernel methods under covariate shift: Data-dependent implicit regularization.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models High-dimensional kernel methods under covariate shift: Data-dependent implicit regularization

Reference 14

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This paper cites Spectral methods for data science: A statistical perspective.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Spectral methods for data science: A statistical perspective

Reference 15

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Benign Overfitting in Out-of-Distribution Generalization of Linear Models On the robustness of the minimim l2 interpolator

Reference 16

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Benign Overfitting in Out-of-Distribution Generalization of Linear Models Learning bounds for importance weighting

Reference 17

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Benign Overfitting in Out-of-Distribution Generalization of Linear Models Genetic algorithms applied to the selection of factors in principal component regression

Reference 18

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Benign Overfitting in Out-of-Distribution Generalization of Linear Models High-dimensional asymptotics of prediction: Ridge regression and classification

Reference 19

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Benign Overfitting in Out-of-Distribution Generalization of Linear Models Factor augmented sparse throughput deep relu neural networks for high dimensional regression

Reference 20

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Benign Overfitting in Out-of-Distribution Generalization of Linear Models Factor-adjusted regularized model selection

Reference 21

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Benign Overfitting in Out-of-Distribution Generalization of Linear Models Robust high dimensional factor models with applications to statistical machine learning

Reference 22

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Benign Overfitting in Out-of-Distribution Generalization of Linear Models On the Provable Advantage of Unsupervised Pretraining

Reference 23

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Benign Overfitting in Out-of-Distribution Generalization of Linear Models Maximum likelihood estimation is all you need for well-specified covariate shift

Reference 24

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Benign Overfitting in Out-of-Distribution Generalization of Linear Models When do neural networks outperform kernel methods? Advances in Neural Information Processing Systems, 33: 0 14820--14830, 2020

Reference 25

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Benign Overfitting in Out-of-Distribution Generalization of Linear Models Linearized two-layers neural networks in high dimension

Reference 26

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Benign Overfitting in Out-of-Distribution Generalization of Linear Models Domain adaptation for medical image analysis: a survey

Reference 27

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Benign Overfitting in Out-of-Distribution Generalization of Linear Models Some cautionary notes on the use of principal components regression

Reference 28

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Benign Overfitting in Out-of-Distribution Generalization of Linear Models On the value of target data in transfer learning

Reference 29

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Benign Overfitting in Out-of-Distribution Generalization of Linear Models On the Benefits of Over-parameterization for Out-of-Distribution Generalization

Reference 30

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Benign Overfitting in Out-of-Distribution Generalization of Linear Models Surprises in high-dimensional ridgeless least squares interpolation

Reference 31

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Benign Overfitting in Out-of-Distribution Generalization of Linear Models Benchmarking Neural Network Robustness to Common Corruptions and Perturbations

Reference 32

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Benign Overfitting in Out-of-Distribution Generalization of Linear Models The many faces of robustness: A critical analysis of out-of-distribution generalization

Reference 33

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Benign Overfitting in Out-of-Distribution Generalization of Linear Models Alternative principal components regression procedures for dendrohydrologic reconstructions

Reference 34

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Benign Overfitting in Out-of-Distribution Generalization of Linear Models Improved principal component regression for face recognition under illumination variations

Reference 35

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Benign Overfitting in Out-of-Distribution Generalization of Linear Models Investigation of alternative regressions: Some practical examples

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Benign Overfitting in Out-of-Distribution Generalization of Linear Models Two case studies in the application of principal component analysis

Reference 37

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Benign Overfitting in Out-of-Distribution Generalization of Linear Models A note on the use of principal components in regression

Reference 38

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raw_fallback, observed 2026-08-11T12:18:17.203501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.443233Z digest=sha256:d01815a8cc40949eccd4bca732b794e2eeecac6dff5f39dcce9cd018e81637fd

Observation e5aec3bc-dcae-49d6-a9e0-67dc96b966a3 · outbound

This paper cites Double descent and overfitting under noisy inputs and distribution shift for linear denoisers.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Double descent and overfitting under noisy inputs and distribution shift for linear denoisers

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:18:17.190463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.446710Z digest=sha256:cd9f8b5d87478666ff98bc49444ed21cd5992f820f5954db2f7c9646a5f5ed54

Observation f32c4a00-66b4-4095-9417-a92d1220d02b · outbound

This paper cites Multivariate concentration determination using principal component regression with residual analysis.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Multivariate concentration determination using principal component regression with residual analysis

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:18:17.174035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.450247Z digest=sha256:e566d12bda879a188c46d298e85395925dfc97cf90c0d84729575622517e109b

Observation 52f8cb3d-61ed-4b1b-bb6b-33da645abf48 · outbound

This paper cites The optimal ridge penalty for real-world high-dimensional data can be zero or negative due to the implicit ridge regularization.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models The optimal ridge penalty for real-world high-dimensional data can be zero or negative due to the implicit ridge regularization

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:18:17.161624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.453608Z digest=sha256:ac4f053027147caa1abbf27c4a83fdc6560aa95ba03ecb33d5f1a402ed0dfc72

Observation e699ea1c-de78-4a7d-8431-566f76ee8214 · outbound

This paper cites Uniform convergence of interpolators: Gaussian width, norm bounds and benign overfitting.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Uniform convergence of interpolators: Gaussian width, norm bounds and benign overfitting

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:18:17.147584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.456996Z digest=sha256:605c24ead7d3d9b3c5ba700047f1df5212e2453c0b597b4dc080c6b916945aa3

Observation b0a87836-b0ee-45ff-8eda-aafb11bea6f6 · outbound

This paper cites Wilds: A benchmark of in-the-wild distribution shifts.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Wilds: A benchmark of in-the-wild distribution shifts

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-11T12:18:16.460326Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:18:16.460326Z digest=sha256:f9f40a9ba1d3a8ee87cd1d70a51ec66e76c2b2d22825713fa00e1c9d7372567a

Observation 10cf9f20-19c8-49b7-9ac7-988f1cdcd256 · outbound

This paper cites Marginal singularity, and the benefits of labels in covariate-shift.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Marginal singularity, and the benefits of labels in covariate-shift

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:18:17.128315Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.463894Z digest=sha256:7f33d61ddd1f43ef6bd78a00b8a5a8a133b856a89b8aeed7fc30a908b75cbbb3

Observation 7027bf90-9e64-4157-ae68-02fc218b3bfd · outbound

This paper cites Forecasting of air quality in delhi using principal component regression technique.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Forecasting of air quality in delhi using principal component regression technique

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:18:17.116241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.467436Z digest=sha256:94a28f1caf9e1e5118d07c8167dadf03d6cc62c4046408f0a4a8c2b831d56f4a

Observation 79a4cc3c-a656-4443-9617-b032b046f639 · outbound

This paper cites Near-optimal linear regression under distribution shift.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Near-optimal linear regression under distribution shift

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-11T12:18:16.471348Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:18:16.471348Z digest=sha256:c07ad4992398e01f65722e20f8fbcb146644ce2a743f708d0a9fa5866ed4354d

Observation 770550d2-b50f-47c7-9156-9b46afd2ac0a · outbound

This paper cites On the multiple descent of minimum-norm interpolants and restricted lower isometry of kernels.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models On the multiple descent of minimum-norm interpolants and restricted lower isometry of kernels

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:18:17.093893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.475670Z digest=sha256:7707eb4adb0b9116b43c42e68d719d55e372ec9243e8c4936b4f58b2f5f8d5b7

Observation 925a40fa-a122-405e-a7ed-7efaff9c714a · outbound

This paper cites Principal component regression analysis with spss.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Principal component regression analysis with spss

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:18:17.078448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.479185Z digest=sha256:c6b7b38171b6bb255432b204256ecfad06c57ff165d3bc7efcd87e7f2e374d68

Observation 051e1537-b0b4-4738-92b2-28c9a99c99af · outbound

This paper cites Optimally tackling covariate shift in rkhs-based nonparametric regression.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Optimally tackling covariate shift in rkhs-based nonparametric regression

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-11T12:18:16.483764Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:18:16.483764Z digest=sha256:1e497de4a91527221e1ab9ebf57a31d88889573eabc26443c0fe73e0038e7484

Observation f3cabded-c99d-4144-af34-54fdf043b2ae · outbound

This paper cites Minimum-norm interpolation under covariate shift.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Minimum-norm interpolation under covariate shift

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:18:17.057799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.487626Z digest=sha256:e62aa77c0afd8b0c04b28dfbbba3c6f33ff4890604c2eada1ba9b143820f1693

Observation 154dbe28-452e-4145-9133-3b90ac5df0ec · outbound

This paper cites Principal components regression in exploratory statistical research.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Principal components regression in exploratory statistical research

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:18:17.044898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.491169Z digest=sha256:04c40b864dd57620578ea7aa56b16008406fc31bd5fa51ee56a8e1440eae0d96

Observation 87d3cfc4-5488-45c9-9938-1a0ef9952d1b · outbound

This paper cites The generalization error of random features regression: Precise asymptotics and the double descent curve.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models The generalization error of random features regression: Precise asymptotics and the double descent curve

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-11T12:18:16.495859Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:18:16.495859Z digest=sha256:a54417be8bfb226bed41eaa9a3afc28a362838741726af3b9e1e96e73126d8a8

Observation 54f6bb04-1da3-4f2c-bd90-000023ddb3a0 · outbound

This paper cites Generalization error of random feature and kernel methods: hypercontractivity and kernel matrix concentration.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Generalization error of random feature and kernel methods: hypercontractivity and kernel matrix concentration

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-11T12:18:16.500281Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:18:16.500281Z digest=sha256:9e5457d69dd589a422c0be6b7424e5b41ef821c9784ef296670f9186bb41794a

Observation 8b47450e-38fd-4bdc-aaab-06ec5af6f1cf · outbound

This paper cites Accuracy on the line: on the strong correlation between out-of-distribution and in-distribution generalization.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Accuracy on the line: on the strong correlation between out-of-distribution and in-distribution generalization

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:18:17.018757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.503904Z digest=sha256:1a4e5061b7a7829822f30efb8400772967d927c10e2dc6e0e08977acaac333eb

Observation 5593328a-32c4-4ed4-a876-9e183d8c9c79 · outbound

This paper cites The interpolation phase transition in neural networks: Memorization and generalization under lazy training.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models The interpolation phase transition in neural networks: Memorization and generalization under lazy training

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:18:17.008045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.507141Z digest=sha256:4ed9e2d6adf69f00da14befd1ec2c304043069409fdfb47367325e424b2640fd

Observation 5f80ba5f-a147-4cd1-a578-b28f98e869bd · outbound

This paper cites Minimax lower bounds for transfer learning with linear and one-hidden layer neural networks.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Minimax lower bounds for transfer learning with linear and one-hidden layer neural networks

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:18:16.997426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.510760Z digest=sha256:d154bfdb8c7c81b2ac3bbc60a8e13ed691e463027fe65f218dea063bc9632fd8

Observation 3e2718f6-0087-4476-bc8d-77a949895b67 · outbound

This paper cites Harmless interpolation of noisy data in regression.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Harmless interpolation of noisy data in regression

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-11T12:18:16.514167Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:18:16.514167Z digest=sha256:1d6507f397f396590082a24304f381c71ef6fc4018ef169d85f28a5c749bc821

Observation 479b8bc1-2c85-485f-b293-3704b1e58226 · outbound

This paper cites Principal component regression in nir analysis: viewpoints, background details and selection of components.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Principal component regression in nir analysis: viewpoints, background details and selection of components

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:18:16.980770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.517605Z digest=sha256:468c6615a088eba5433a4f7c4a734fd45e83a488df093628c4f52c327ae17e29

Observation 6b40aeb6-951e-4bd7-9368-04ee22777304 · outbound

This paper cites More Data Can Hurt for Linear Regression: Sample-wise Double Descent.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models More Data Can Hurt for Linear Regression: Sample-wise Double Descent

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-11T12:18:16.521750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:18:16.521750Z digest=sha256:1dd5ddbe1305dcd6fe0725364941088c2273bee9ef8fb8478909f19c3258cc88

Observation d1615f8c-d1f3-4ada-96cb-1d7b6f9b201e · outbound

This paper cites In defense of uniform convergence: Generalization via derandomization with an application to interpolating predictors.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models In defense of uniform convergence: Generalization via derandomization with an application to interpolating predictors

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:18:16.971236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.527446Z digest=sha256:914290db512e421242dc32d2de1f996bf38cb7afe49bf42f567212ba9b73f3ea

Observation 158a172f-4874-473b-9f25-1f42c0e19b79 · outbound

This paper cites Manifold regularization and semi-supervised learning: Some theoretical analyses.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Manifold regularization and semi-supervised learning: Some theoretical analyses

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-11T12:18:16.532561Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:18:16.532561Z digest=sha256:707a6a8c181c52eb39431431dda247018a81c7b1d84601b8f45bddd85b1063d6

Observation ed255284-41d4-4f61-8bca-31a16515ea8d · outbound

This paper cites A new similarity measure for covariate shift with applications to nonparametric regression.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models A new similarity measure for covariate shift with applications to nonparametric regression

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:18:16.954722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.536061Z digest=sha256:b04839686f2737474847a7f137f2b9243d34703f1d967b9d9611bfe65dfb9f25

Observation 836c816b-9a0b-4c12-ae82-2d60e4647abb · outbound

This paper cites Do imagenet classifiers generalize to imagenet? In International conference on machine learning, pages 5389--5400.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Do imagenet classifiers generalize to imagenet? In International conference on machine learning, pages 5389--5400

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-11T12:18:16.539801Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:18:16.539801Z digest=sha256:b23ff71c3deec02921a3ebf3283f15f9f682ee6313022d702e86f51109c9441d

Observation 2ffc7d44-298f-45a9-862e-cb5411dd2017 · outbound

This paper cites Asymptotics of ridge (less) regression under general source condition.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Asymptotics of ridge (less) regression under general source condition

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-11T12:18:16.543670Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:18:16.543670Z digest=sha256:07216b5bc43b71323c9263eaec0c768225db31818043ca46a74adb9df1f00831

Observation 2002c3b9-bc1a-4185-aa89-cce984d2efa5 · outbound

This paper cites The implicit bias of benign overfitting.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models The implicit bias of benign overfitting

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:18:16.931018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.547509Z digest=sha256:4d10199a815b05963b36da70edc06c55bb579dbf8f247fe529b7c17509635a2a

Observation 339ef73d-6dcb-4d6d-9dda-54d3abb801d3 · outbound

This paper cites Improving predictive inference under covariate shift by weighting the log-likelihood function.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Improving predictive inference under covariate shift by weighting the log-likelihood function

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-11T12:18:16.551074Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:18:16.551074Z digest=sha256:20df9f65bfc4a5ef170f72e1c5a86ff347f771711d9a99425979677033b26058

Observation 9f16c55b-70ec-4797-80d8-ab955fa3ba73 · outbound

This paper cites More is Better in Modern Machine Learning: when Infinite Overparameterization is Optimal and Overfitting is Obligatory.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models More is Better in Modern Machine Learning: when Infinite Overparameterization is Optimal and Overfitting is Obligatory

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-11T12:18:16.554591Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:18:16.554591Z digest=sha256:cafb6e3b473330aa8eab6a56fe1f93880db9fa13f1103a528da6cce1659fd8c0

Observation c0fa4218-c4bd-48b6-8b60-16b0352ef066 · outbound

This paper cites Forecasting using principal components from a large number of predictors.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Forecasting using principal components from a large number of predictors

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:18:16.911636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.559575Z digest=sha256:ae1de85734c9b39ed994cb903706e396aecc1616b3dfdb77023a09eebfa05cb4

Observation 2d119888-04cd-4102-af42-8b1ec0f08d4f · outbound

This paper cites A correlation principal component regression analysis of nir data.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models A correlation principal component regression analysis of nir data

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:18:16.900223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.563135Z digest=sha256:622b9fe24eeb3f4cc291270e1106e16edb7b411ff46b257ddfd79ac6eec7b9e7

Observation aa23c5e3-1d37-474f-9c8f-bb324b9caf91 · outbound

This paper cites Overparameterization improves robustness to covariate shift in high dimensions.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Overparameterization improves robustness to covariate shift in high dimensions

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:18:16.889724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.566961Z digest=sha256:494d583f3e119facb2179e29f3992eea7eb711c19c2d145a9998c891a2334b8e

Observation 6abe1e79-416d-48eb-9f0a-8a8970ffba2d · outbound

This paper cites Provable meta-learning of linear representations.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Provable meta-learning of linear representations

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:18:16.877819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.570420Z digest=sha256:e8f5f5ed8b2975b7b3c9c3fe4b1f65d81f05b48dea20f614f992da4f6064a1c7

Observation 54c5f259-0a3a-45c7-afc7-cae5536eb493 · outbound

This paper cites Bartlett.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Bartlett

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:18:16.865578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.574030Z digest=sha256:8c7c398303fbac7c7c9d58673ef40cc06f730a984c74e6669c0ca05253f71c85

Observation 9501cf50-7550-4cf7-a599-1b6135712bd3 · outbound

This paper cites An inequality for trace ideals.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models An inequality for trace ideals

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:18:16.854803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.577906Z digest=sha256:fc4e7829875c707ec3e5a343f14761979c64a7869e4da884f3d215534ae46fe9

Observation eb5848fe-8a41-466a-8792-fd385fd97a34 · outbound

This paper cites Introduction to the non-asymptotic analysis of random matrices.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Introduction to the non-asymptotic analysis of random matrices

Reference 74

Resolution
unresolved
no resolver link, observed 2026-08-11T12:18:16.581331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:18:16.581331Z digest=sha256:265ccb414c4a642bb649087aedd46f3578f639e0840078620d4ba416e3be0aa2

Observation a794e6c6-cdd8-49b5-960e-fe3b8977b800 · outbound

This paper cites High-dimensional probability: An introduction with applications in data science, volume 47.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models High-dimensional probability: An introduction with applications in data science, volume 47

Reference 75

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This paper cites Principal component regression, ridge regression and ridge principal component regression in spectroscopy calibration.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Principal component regression, ridge regression and ridge principal component regression in spectroscopy calibration

Reference 76

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This paper cites Perturbation theory for pseudo-inverses.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Perturbation theory for pseudo-inverses

Reference 77

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This paper cites Assaying out-of-distribution generalization in transfer learning.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Assaying out-of-distribution generalization in transfer learning

Reference 78

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This paper cites On the optimal weighted l2 regularization in overparameterized linear regression.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models On the optimal weighted l2 regularization in overparameterized linear regression

Reference 79

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This paper cites On the number of variables to use in principal component regression.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models On the number of variables to use in principal component regression

Reference 80

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Observation 339644f8-2bff-47a2-8f3a-72da10ac2083 · outbound

This paper cites Understanding Why Generalized Reweighting Does Not Improve Over ERM.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Understanding Why Generalized Reweighting Does Not Improve Over ERM

Reference 81

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This paper cites A class of geometric structures in transfer learning: Minimax bounds and optimality.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models A class of geometric structures in transfer learning: Minimax bounds and optimality

Reference 82

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Observation aa7be798-e666-483d-87e0-85ced2b635d1 · outbound

This paper cites On uniform convergence and low-norm interpolation learning.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models On uniform convergence and low-norm interpolation learning

Reference 83

Resolution
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Observation 3aa1f6eb-d3f1-4776-aac0-d82fcffa0618 · outbound

This paper cites Unsupervised domain adaptation for semantic segmentation via class-balanced self-training.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Unsupervised domain adaptation for semantic segmentation via class-balanced self-training

Reference 84

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This paper cites @esa (Ref.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models @esa (Ref

Reference 85

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Benign Overfitting in Out-of-Distribution Generalization of Linear Models Unresolved cited work

Reference 86

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Observation bb60194a-e6e4-435c-a0f6-1213d6e74928 · outbound

This paper cites On Model Identification and Out-of-Sample Prediction of Principal Component Regression: Applications to Synthetic Controls.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models On Model Identification and Out-of-Sample Prediction of Principal Component Regression: Applications to Synthetic Controls

Reference 87

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Pith citing papers

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