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Paper Citation Record · LEDGER

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

As of 19 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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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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This paper cites Laplacian eigenmaps for dimensionality reduction and data representation.

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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This paper cites Project cost estimation using principal component regression.

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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This paper cites On the Provable Advantage of Unsupervised Pretraining.

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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This paper cites When do neural networks outperform kernel methods? Advances in Neural Information Processing Systems, 33: 0 14820--14830, 2020.

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 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.443233Z digest=sha256:a249015c16bc30fe7581b4d8bd224b8ae97a201e105c259f4782f642cb593b44

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 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.446710Z digest=sha256:8d076c6f63bb7b2d9db6848cc318aeb037751789a0ca0fec44c5e00203b6d74b

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 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.450247Z digest=sha256:e8fd64c664bab1151c7365a78cba513b3a8e9c9661624669d3c78bdffa4c7504

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 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.453608Z digest=sha256:d45f9fdf6c9d4067e79ce2ea93c4a40dc146f580821026a80071f550fb9fcafc

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 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.456996Z digest=sha256:18923a84e7280f524af885f37273c2f3587980c49d587fd707b0c91f8893d212

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:f17825757507ba5f3f1764ac8c93dee791345d60ac7033a1a7de71d66de2cebc

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 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.463894Z digest=sha256:160e9a523d616443ff3dd35924435c3e292261024dcd39679d4d9b2ade9c179b

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 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.467436Z digest=sha256:47b13abf57e7184ab1a6e2e443a726917f40a3f17298b00d3cb901e5a662e0cb

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=sha256:02b788150aee0782035f6b714dab6e3f99fe0304cb6b608c094dee2f6032522e

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 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.475670Z digest=sha256:6cc36464f18ef1d25333591d2380edbad71ee53d76d8cb1c0432f614579ea13c

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 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.479185Z digest=sha256:a4d9304c1f9c8da9853c65687f2f736e52fa5db2ca287bba5cb1c65e40d04077

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=sha256:7cc8e7cb791e3315198c0315c0f3a29986ec4c89ac1d4d790ca47052c5425108

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 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.487626Z digest=sha256:2ceb8a52c96fdf3952d5135286ab4c4ec0c4c58660853b7ee57b8a95e602e3ce

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 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.491169Z digest=sha256:145eac741fb6aa996a01fa3a66d9c4dd590c6efda0862437e77f1a8dc1d2af59

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=sha256:227cf38a45e0f304313a8619a5ea0ebf30c6d1a8bd26c8c56a6641eb8262d051

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=sha256:165988acd40232e6791c9696db773b3826c8bf48391e6538c51f7149b4e32691

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 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.503904Z digest=sha256:60127028e49e067612f6722c1c1d41fcb47872ee371f95fa6027e873ebc91e9b

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 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.507141Z digest=sha256:156e964bf5ef05986b1e115df0347cf16cd8697285aebe3c58334a199e9617cc

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 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.510760Z digest=sha256:ab7054c08ba0d4f5117ab78be62527bc11aa4e57cccc5cd9a4cd53834b719be6

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:bcd053ba972755afc02dbbeafbcf357b5ad3b236dd5b932801880336215afd7c

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 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.517605Z digest=sha256:455bdc90806efb905679bc5c91243e887ee0393353df1f4ab998e1cf84106de9

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=sha256:61258a51d8b4da51e582a204ae25b1d504debb2c15193f7c61ed52be4797ea53

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 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.527446Z digest=sha256:d7332ec5e6b3b1f68e60cadb7234dbcef6635a217e86e7ea49e5a2967f894646

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:a6f00e908c5259b1a2a32fe981396aade4e10e152196926213985cd6535da2d2

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 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.536061Z digest=sha256:1792a77e456b3b9b6b3ec852cba2dcc74d4f4ccc83e7a0bc05d7b3b99b5bd18d

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:e5d7b0f7931a5ede77458d24cd25607236bf6d8055afa68b361d4c9d85e2218c

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:d0cb86f7b5705725d12b191b4659caa076fec4ecb3166384777297127e315001

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 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.547509Z digest=sha256:1236f51fd0ae7a3f58184b802f18717ac06b2de4c2d731021c95c53ebf6e715e

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=sha256:6b81d50a6c6d1a8ef3db6f93951ec6429200d5d1cad7394e89ebc1891d7b922f

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=sha256:06a38b0e57528a40ded7b885c150af43bccb88e83f82ad6ae5b8da5eaa678d93

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 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.559575Z digest=sha256:7e205df4e85eb256c039dd8ed20fbaf351a45911bcdcf343eb2a868e6e023238

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 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.563135Z digest=sha256:50fcef7dcdeabaf856b6298c6c63b5f79f931d4dea379e58269577feef8b6f6e

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 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.566961Z digest=sha256:504f629439b94598155e5e7d5a216b4f761e2214fb1b423bd4e0131fc9de25e2

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 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.570420Z digest=sha256:30fb261bfef0528fe5cc7241abcefe23128c0e50837b3e0f62d297da13df284b

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 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.574030Z digest=sha256:168be1b2902fac675d296dc1dfd6024eb3cf932c1aad176ce6c96247dbbe033a

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 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T12:18:16.577906Z digest=sha256:114d1dfed42a5341210d3df853c221b36d8d9cc95291ffdef06321a90b5b054a

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=sha256:1afa625e43f50ed77bed786bad6511576c81effb7a5866c0111ea57fdff08161

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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Observation 13b13cde-3203-456e-8291-95c4951ff619 · outbound

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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Observation 35dd1de1-6760-4b12-b91c-73968b8d4ee7 · outbound

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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Observation f23e386e-c779-487c-a364-be49753a6681 · outbound

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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Observation 73e6a05a-6ba5-452f-bac9-2b81027ddc8e · outbound

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

Resolution
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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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Observation 49252986-e2fb-4315-baa6-c17de4101220 · outbound

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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Source-reported events for the cited work

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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

Resolution
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Observation bcb72342-93fa-4be0-a13e-e5bb548ae964 · outbound

This paper cites @esa (Ref.

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

Reference 85

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Observation 90a5cbd8-46ab-45dd-9467-8644548e264e · outbound

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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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