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Paper Citation Record · LEDGER

The Fourth Quadrant: A Stylized View of Benign Misfitting

As of 16 August 2026, this Paper Citation Record lists 100 of 231 outbound references and 0 inbound Pith citation observations for arXiv:2608.01032.

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

pith.paper-citation-record.v1
2608.01032 v1

Coverage vector

measured 100 of 231 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T00:43:13.551631Z

measured 100 of 100 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

100 of 231 outbound references displayed

  • verified exact7
  • verified fuzzy0
  • unresolved85
  • parse uncertain0
  • malformed identifier4
  • metadata mismatch4

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c6bb50b1-53bf-4365-acf8-e84f932d14ce · outbound

This paper cites Brendan McMahan, Ilya Mironov, Kunal Talwar, and Li Zhang.

The Fourth Quadrant: A Stylized View of Benign Misfitting Brendan McMahan, Ilya Mironov, Kunal Talwar, and Li Zhang

Reference 1

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Observation 9a68094e-96e6-4ae4-ba0b-6fa6e82f8f8e · outbound

This paper cites The merged-staircase property: A necessary and nearly sufficient condition for SGD learning of sparse functions on two-layer neural networks.

The Fourth Quadrant: A Stylized View of Benign Misfitting The merged-staircase property: A necessary and nearly sufficient condition for SGD learning of sparse functions on two-layer neural networks

Reference 2

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Observation f93a7245-9a0d-4889-99c8-0c56ecb10b45 · outbound

This paper cites SGD learning on neural networks: Leap complexity and saddle-to-saddle dynamics.

The Fourth Quadrant: A Stylized View of Benign Misfitting SGD learning on neural networks: Leap complexity and saddle-to-saddle dynamics

Reference 3

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Observation 03b56ee0-2d43-4e49-8902-5bfafd6b9df6 · outbound

This paper cites an unresolved cited work.

The Fourth Quadrant: A Stylized View of Benign Misfitting Unresolved cited work

Reference 4

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source=pdf_text observed=2026-08-06T00:43:04.434013Z digest=sha256:6dde1b49f2ddd253132ec9d0822aacebe1c9e1c658985744957afaa3cffe80d2

Observation e8361369-026c-4f1b-a70d-0d9a0b147b8b · outbound

This paper cites Advani and Andrew M.

The Fourth Quadrant: A Stylized View of Benign Misfitting Advani and Andrew M

Reference 5

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source=pdf_text observed=2026-08-06T00:43:04.536617Z digest=sha256:1fc4bda065dc42746808b04f145c93ff4d5134cf1c03f2bd2e0f4b8e82f9e208

Observation 0a87b232-727f-49f8-8eb9-eb6f6fff960e · outbound

This paper cites Understanding the unstable convergence of gradient descent.

The Fourth Quadrant: A Stylized View of Benign Misfitting Understanding the unstable convergence of gradient descent

Reference 6

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Observation 5d03c576-5709-4630-88a2-9798a1b3d89e · outbound

This paper cites Zico Kolter, and Ryan J.

The Fourth Quadrant: A Stylized View of Benign Misfitting Zico Kolter, and Ryan J

Reference 7

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source=pdf_text observed=2026-08-06T00:43:04.799424Z digest=sha256:da41ef7c36779c8bb87f7765f9f13f40d48cf66450f6702af134d3756388afac

Observation e909b75d-fe91-4635-b0f7-a37fc788092e · outbound

This paper cites The implicit regularization of stochastic gradient flow for least squares.

The Fourth Quadrant: A Stylized View of Benign Misfitting The implicit regularization of stochastic gradient flow for least squares

Reference 8

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source=pdf_text observed=2026-08-06T00:43:04.869077Z digest=sha256:2e4dc39e016615a11e489cec289a4090bc9efedadccfbc63064bcf4050f1d7b7

Observation 81b6fa84-2c49-4bbe-9c1e-560e6648e9c8 · outbound

This paper cites The space complexity of approximating the frequency moments.Journal of Computer and System Sciences, 58(1):137–147, 1999.

The Fourth Quadrant: A Stylized View of Benign Misfitting The space complexity of approximating the frequency moments.Journal of Computer and System Sciences, 58(1):137–147, 1999

Reference 9

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Observation 9dfb36b1-4ecc-4d64-95e5-7ce5aeb8fa80 · outbound

This paper cites Never go full batch (in stochastic convex optimization).

The Fourth Quadrant: A Stylized View of Benign Misfitting Never go full batch (in stochastic convex optimization)

Reference 10

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Observation 4fa66407-f9d1-447c-9f0b-8637915375bd · outbound

This paper cites SGD generalizes better than GD (and regularization doesn’t help).

The Fourth Quadrant: A Stylized View of Benign Misfitting SGD generalizes better than GD (and regularization doesn’t help)

Reference 11

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Observation 2c4a9ef4-7ea3-42df-ba93-dc047e08c6dd · outbound

This paper cites Thinking outside the ball: Optimal learning with gradient descent for generalized linear stochastic convex optimization.

The Fourth Quadrant: A Stylized View of Benign Misfitting Thinking outside the ball: Optimal learning with gradient descent for generalized linear stochastic convex optimization

Reference 12

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Observation e63286a3-2f27-48d2-b8b0-1ea30217d626 · outbound

This paper cites Edge of stochastic stability: Revisiting the edge of stability for SGD, 2024.

The Fourth Quadrant: A Stylized View of Benign Misfitting Edge of stochastic stability: Revisiting the edge of stability for SGD, 2024

Reference 13

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source=pdf_text observed=2026-08-06T00:43:05.327993Z digest=sha256:7129947606c11de90dd439a2dd28f195587d672de94483936999cb5b1401fb6d

Observation b26bde74-1172-457d-8f1e-38102874da0b · outbound

This paper cites Understanding gradient descent on the edge of stability in deep learning.

The Fourth Quadrant: A Stylized View of Benign Misfitting Understanding gradient descent on the edge of stability in deep learning

Reference 14

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Observation dc1b8b78-18a6-44f6-a55d-f07aa0abdfc0 · outbound

This paper cites Information Complexity of Stochastic Convex Optimization: Applications to Generalization and Memorization.

The Fourth Quadrant: A Stylized View of Benign Misfitting Information Complexity of Stochastic Convex Optimization: Applications to Generalization and Memorization

Reference 15

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Observation 94459c81-6829-4a7d-b3de-be65f227b326 · outbound

This paper cites Robust linear least squares regression.The Annals of Statistics, 39(5):2766–2794, 2011.

The Fourth Quadrant: A Stylized View of Benign Misfitting Robust linear least squares regression.The Annals of Statistics, 39(5):2766–2794, 2011

Reference 16

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Observation bd6a8757-6d73-48e9-85b3-04bd32f57148 · outbound

This paper cites Diggavi, and David N.

The Fourth Quadrant: A Stylized View of Benign Misfitting Diggavi, and David N

Reference 17

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Source-reported events for the cited work

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Observation 0ea40c81-ace8-4ec2-b685-19d0b821897c · outbound

This paper cites Phase transition of the largest eigenvalue for nonnull complex sample covariance matrices.The Annals of Probability, 33(5):1643–1697,.

The Fourth Quadrant: A Stylized View of Benign Misfitting Phase transition of the largest eigenvalue for nonnull complex sample covariance matrices.The Annals of Probability, 33(5):1643–1697,

Reference 18

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Observation 2cf6ae6c-fbc6-40d3-bf69-9b53d4bab8ab · outbound

This paper cites an unresolved cited work.

The Fourth Quadrant: A Stylized View of Benign Misfitting Unresolved cited work

Reference 19

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Observation 2ad0818a-afdf-486f-baec-0156a0080027 · outbound

This paper cites Bartlett, Philip M.

The Fourth Quadrant: A Stylized View of Benign Misfitting Bartlett, Philip M

Reference 20

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Observation a0e64c60-2428-4f9b-a901-b8a2d704be9b · outbound

This paper cites Fit without fear: Remarkable mathematical phenomena of deep learn- ing through the prism of interpolation.Acta Numerica, 30:203–248, 2021.

The Fourth Quadrant: A Stylized View of Benign Misfitting Fit without fear: Remarkable mathematical phenomena of deep learn- ing through the prism of interpolation.Acta Numerica, 30:203–248, 2021

Reference 21

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Observation 2d922e36-5755-4357-85a9-cb0005d0ba99 · outbound

This paper cites Hsu, and Partha P.

The Fourth Quadrant: A Stylized View of Benign Misfitting Hsu, and Partha P

Reference 22

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Observation 787ed768-5e67-412f-b85f-7cc65e738bf3 · outbound

This paper cites an unresolved cited work.

The Fourth Quadrant: A Stylized View of Benign Misfitting Unresolved cited work

Reference 23

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Observation 0fdbe2da-0d12-4fd4-9fb4-e3ba763de915 · outbound

This paper cites Reconciling modern machine- learning practice and the classical bias–variance trade-off.Proceedings of the National Academy of Sciences, 116(32):15849–15854, 2019.

The Fourth Quadrant: A Stylized View of Benign Misfitting Reconciling modern machine- learning practice and the classical bias–variance trade-off.Proceedings of the National Academy of Sciences, 116(32):15849–15854, 2019

Reference 24

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Observation 7500c083-27d6-4971-b442-d22c31fb74a5 · outbound

This paper cites Tsybakov.

The Fourth Quadrant: A Stylized View of Benign Misfitting Tsybakov

Reference 25

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Observation 06eb9d9d-f8ba-4583-af0c-b5a2e82d15e9 · outbound

This paper cites To understand deep learning we need to understand kernel learning.

The Fourth Quadrant: A Stylized View of Benign Misfitting To understand deep learning we need to understand kernel learning

Reference 26

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Observation a2103233-9db3-4c8a-abcb-fce1c2743fd4 · outbound

This paper cites Incremental Gradient, Subgradient, and Proximal Methods for Convex Optimization: A Survey.

The Fourth Quadrant: A Stylized View of Benign Misfitting Incremental Gradient, Subgradient, and Proximal Methods for Convex Optimization: A Survey

Reference 27

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Observation bffaf9aa-4409-4b3c-ab6c-72f121b7fd4d · outbound

This paper cites Learning single-index models with shallow neural networks.

The Fourth Quadrant: A Stylized View of Benign Misfitting Learning single-index models with shallow neural networks

Reference 28

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Observation 2747bd0f-4da8-4641-978a-576854a26518 · outbound

This paper cites Implicit regularization for deep neural networks driven by an Ornstein–Uhlenbeck like process.

The Fourth Quadrant: A Stylized View of Benign Misfitting Implicit regularization for deep neural networks driven by an Ornstein–Uhlenbeck like process

Reference 29

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Observation 1384f0ef-defc-4f76-82ca-fa7c938c261e · outbound

This paper cites Two models of double descent for weak features.SIAM Journal on Mathematics of Data Science, 2(4):1167–1180, 2020.

The Fourth Quadrant: A Stylized View of Benign Misfitting Two models of double descent for weak features.SIAM Journal on Mathematics of Data Science, 2(4):1167–1180, 2020

Reference 30

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Observation 756a1d6e-885b-493f-a82b-0a4a859d39f3 · outbound

This paper cites The tradeoffs of large scale learning.

The Fourth Quadrant: A Stylized View of Benign Misfitting The tradeoffs of large scale learning

Reference 31

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Observation f6718b94-4b92-44be-adc6-cdc5a8714ae6 · outbound

This paper cites Curtis, and Jorge Nocedal.

The Fourth Quadrant: A Stylized View of Benign Misfitting Curtis, and Jorge Nocedal

Reference 32

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source=pdf_text observed=2026-08-06T00:43:07.025745Z digest=sha256:df753fbf599e42001bc05a0858990d2835d67169b0af7045206494f98b96218f

Observation 6499b4cd-5e02-48c3-badf-c1ad267afd71 · outbound

This paper cites Stability and generalization.Journal of Machine Learning Research, 2:499–526, 2002.

The Fourth Quadrant: A Stylized View of Benign Misfitting Stability and generalization.Journal of Machine Learning Research, 2:499–526, 2002

Reference 33

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Observation 96e3f843-f434-4ed5-b990-78a73561a7ad · outbound

This paper cites Euclidean information theory.

The Fourth Quadrant: A Stylized View of Benign Misfitting Euclidean information theory

Reference 34

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Observation 807ead5a-b640-412a-9e83-c9b6b3e06b15 · outbound

This paper cites Bagging predictors.Machine Learning, 24(2):123–140, 1996.

The Fourth Quadrant: A Stylized View of Benign Misfitting Bagging predictors.Machine Learning, 24(2):123–140, 1996

Reference 35

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Observation a980f28c-00eb-4c00-971a-e73b3fd57beb · outbound

This paper cites an unresolved cited work.

The Fourth Quadrant: A Stylized View of Benign Misfitting Unresolved cited work

Reference 36

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raw_fallback, observed 2026-08-06T00:43:28.629442Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 9ff890a8-cc8d-474b-85ad-17e8f0333b0f · outbound

This paper cites Survey on algorithms for multi-index models.Statistical Science, 40(3):378–391, 2025.

The Fourth Quadrant: A Stylized View of Benign Misfitting Survey on algorithms for multi-index models.Statistical Science, 40(3):378–391, 2025

Reference 37

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source=pdf_text observed=2026-08-06T00:43:07.566547Z digest=sha256:4e2357e346b5318139d868ab702eb2f0e1037cfa1ed0b115e1e33c7e4d6ada5f

Observation 93efd1e8-e860-4cb9-b52c-ccedce42edb7 · outbound

This paper cites Proper learning, Helly number, and an optimal SVM bound.

The Fourth Quadrant: A Stylized View of Benign Misfitting Proper learning, Helly number, and an optimal SVM bound

Reference 38

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source=pdf_text observed=2026-08-06T00:43:07.249076Z digest=sha256:3391e6a5d73d32180c34fbc2c4af629b6b3769b9822f928cc5346cd2fbe76a14

Observation b45a8b21-9802-4f96-a470-ccf438d3e8e7 · outbound

This paper cites A universal law of robustness via isoperimetry.

The Fourth Quadrant: A Stylized View of Benign Misfitting A universal law of robustness via isoperimetry

Reference 39

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source=pdf_text observed=2026-08-06T00:43:07.800234Z digest=sha256:a70e02936064bf2ce2710070af319dc61c8ed0c3494fec212d62c46c6e1a7dea

Observation 0dbfddd8-552c-47a3-a0eb-dd9ee1e1fe64 · outbound

This paper cites All ERMs can fail in stochastic convex optimization lower bounds in linear dimension, 2026.

The Fourth Quadrant: A Stylized View of Benign Misfitting All ERMs can fail in stochastic convex optimization lower bounds in linear dimension, 2026

Reference 40

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source=pdf_text observed=2026-08-06T00:43:07.899650Z digest=sha256:07733be722b0f5f24d78b0e0adda4ff98bdc375909a6bc4212048da59b474355

Observation 1dba8a15-1a16-486d-985d-80bf731d2575 · outbound

This paper cites The secret sharer: Evaluating and testing unintended memorization in neural networks.

The Fourth Quadrant: A Stylized View of Benign Misfitting The secret sharer: Evaluating and testing unintended memorization in neural networks

Reference 41

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source=pdf_text observed=2026-08-06T00:43:07.986437Z digest=sha256:385835f6f8825da6493ebacddc838b1a7d37aa66498b4cdaaef0faae2c7a31f6

Observation f9b8f9f7-0cc6-4359-800d-79406e058005 · outbound

This paper cites Veeravalli.

The Fourth Quadrant: A Stylized View of Benign Misfitting Veeravalli

Reference 42

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raw_fallback, observed 2026-08-06T00:43:28.393780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T00:43:07.682068Z digest=sha256:5797740e568bcb8949f2ab7d8b99918823ab54238d47113c2bf06964f7673c19

Observation 6640581c-a1ac-4199-9a58-4eb641099b6a · outbound

This paper cites Membership inference attacks from first principles.

The Fourth Quadrant: A Stylized View of Benign Misfitting Membership inference attacks from first principles

Reference 43

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source=pdf_text observed=2026-08-06T00:43:08.203011Z digest=sha256:c28a88d857ec417fb4a82a2c1715c82f008640bc740a76ff99d25fed6bd6254f

Observation d5ad1ba1-184c-4f2f-a39d-3b531b5874c9 · outbound

This paper cites The sample complexity of ERMs in stochastic convex optimization.

The Fourth Quadrant: A Stylized View of Benign Misfitting The sample complexity of ERMs in stochastic convex optimization

Reference 44

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source=pdf_text observed=2026-08-06T00:43:08.284763Z digest=sha256:8730abcbcdfd9479e426e3493db4a9d8b2beb904af000792f4a79c2c2593af99

Observation 30c0cc34-51be-4cc1-80cc-1c2bdf1c8d74 · outbound

This paper cites an unresolved cited work.

The Fourth Quadrant: A Stylized View of Benign Misfitting Unresolved cited work

Reference 45

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source=pdf_text observed=2026-08-06T00:43:08.360292Z digest=sha256:824f9384a910612c751e0a2ebc7786ede0cb893f19de807f3abbd601f5232b45

Observation c3dabff3-5f34-4ddf-bca9-3e805a5b7cff · outbound

This paper cites Extracting training data from large language models.

The Fourth Quadrant: A Stylized View of Benign Misfitting Extracting training data from large language models

Reference 46

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source=pdf_text observed=2026-08-06T00:43:08.079302Z digest=sha256:883a6ef465d97cc511f5257174b50330d848c67e155c188edbe7c692b276a548

Observation f5701117-578e-48f9-98a3-a8ceeffc9b78 · outbound

This paper cites Understanding gradient clipping in private SGD: A geometric perspective.

The Fourth Quadrant: A Stylized View of Benign Misfitting Understanding gradient clipping in private SGD: A geometric perspective

Reference 47

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source=pdf_text observed=2026-08-06T00:43:08.513441Z digest=sha256:312b52475c2f25450964c67445703174362ee1807c3834565aa31b7d04f0e2c5

Observation c90c737f-82b9-4b55-ac7b-b52c5b8244f7 · outbound

This paper cites From One-Pass SGD to Data Reuse: Mini-Batch Scaling Laws in Sketched Linear Regression.

The Fourth Quadrant: A Stylized View of Benign Misfitting From One-Pass SGD to Data Reuse: Mini-Batch Scaling Laws in Sketched Linear Regression

Reference 48

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source=pdf_text observed=2026-08-06T00:43:08.595282Z digest=sha256:88d099f8d780b065cd896ee3e9581e321862ae43be10abd61a08403e4296538d

Observation ac67c988-0181-4e24-891e-b07c7abcaf53 · outbound

This paper cites On the robustness of minimum norm interpolators and regularized empirical risk minimizers.The Annals of Statistics, 50(4): 2306–2333, 2022.

The Fourth Quadrant: A Stylized View of Benign Misfitting On the robustness of minimum norm interpolators and regularized empirical risk minimizers.The Annals of Statistics, 50(4): 2306–2333, 2022

Reference 49

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doi, observed 2026-08-06T00:43:24.343619Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T00:43:08.697362Z digest=sha256:0958e277ebe7082ac4748d3e9a24eef36d3db8e445e2f9afb770b24143939c13

Observation dd7f8604-0d29-442e-9d09-1ceb8a1bf0e7 · outbound

This paper cites Sarwate, and Kaushik Sinha.

The Fourth Quadrant: A Stylized View of Benign Misfitting Sarwate, and Kaushik Sinha

Reference 50

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source=pdf_text observed=2026-08-06T00:43:08.414251Z digest=sha256:e5d699afaecd86af8160b83c1022d585a0270edfa05b9a49f2777ddc526206a5

Observation 86e3251c-3318-44f0-8787-91a1faafccff · outbound

This paper cites Cohen, Simran Kaur, Yuanzhi Li, J.

The Fourth Quadrant: A Stylized View of Benign Misfitting Cohen, Simran Kaur, Yuanzhi Li, J

Reference 51

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source=pdf_text observed=2026-08-06T00:43:08.895415Z digest=sha256:670a7d460bfdbb9bf15b81effdae1d362368825cf70b6865c466d433520eb781

Observation d40be81b-e5bc-4b75-ae3a-80165648934e · outbound

This paper cites High-dimensional limit of one-pass SGD on least squares.

The Fourth Quadrant: A Stylized View of Benign Misfitting High-dimensional limit of one-pass SGD on least squares

Reference 52

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verified exact
local_arxiv, observed 2026-08-06T00:43:28.022592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T00:43:08.999423Z digest=sha256:0910694f000af5fa0f66cf8dd8d5825c4acee8a8da71ec984949589887e8f532

Observation 2e583e8e-7678-4bc4-8238-083cf5819d16 · outbound

This paper cites Cubuk, Barret Zoph, Dandelion Mane, Vijay Vasudevan, and Quoc V.

The Fourth Quadrant: A Stylized View of Benign Misfitting Cubuk, Barret Zoph, Dandelion Mane, Vijay Vasudevan, and Quoc V

Reference 53

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source=pdf_text observed=2026-08-06T00:43:09.095098Z digest=sha256:873a374802a18ae500083e484b16b83357fbb8967fff389b2935db21859372b7

Observation 87222f27-494f-489b-90e0-a05c19cc1f0a · outbound

This paper cites Choquette-Choo, Florian Tram` er, Nicholas Carlini, and Nicolas Papernot.

The Fourth Quadrant: A Stylized View of Benign Misfitting Choquette-Choo, Florian Tram` er, Nicholas Carlini, and Nicolas Papernot

Reference 54

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source=pdf_text observed=2026-08-06T00:43:08.784611Z digest=sha256:371e9a19cc28fdfb7cc3e1a71e14a81e6715949f7b480958c8eb4bb8e127f248

Observation 7a2c4d18-6c15-4b1e-b879-3387d78cf3fd · outbound

This paper cites A Farewell to the Bias-Variance Tradeoff? An Overview of the Theory of Overparameterized Machine Learning.

The Fourth Quadrant: A Stylized View of Benign Misfitting A Farewell to the Bias-Variance Tradeoff? An Overview of the Theory of Overparameterized Machine Learning

Reference 55

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source=pdf_text observed=2026-08-06T00:43:09.319426Z digest=sha256:400fb2c3caa4f14b30b34477c9e6fc3a9d1787348f35b53b0ead13110732698e

Observation 8d3e389f-c4a2-4826-b35b-fff402884853 · outbound

This paper cites Oliveira.

The Fourth Quadrant: A Stylized View of Benign Misfitting Oliveira

Reference 56

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source=pdf_text observed=2026-08-06T00:43:09.438741Z digest=sha256:298dceb709d9a21c77eacce8b9dd0ac02f6061775fe4ba179a0ca539f3bd2638

Observation f7a0d408-89b5-4ce4-b85e-50b6a2f7557b · outbound

This paper cites Sharp minima can generalize for deep nets.

The Fourth Quadrant: A Stylized View of Benign Misfitting Sharp minima can generalize for deep nets

Reference 57

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source=pdf_text observed=2026-08-06T00:43:09.575239Z digest=sha256:b14fb374c70d658548f2c67794d04a18ec1e53f64d9c4ee7135dffeac55c34aa

Observation 97fc50f7-01a8-45d4-ba8d-47cc966abf5f · outbound

This paper cites Self-stabilization: The implicit bias of gradient descent at the edge of stability.

The Fourth Quadrant: A Stylized View of Benign Misfitting Self-stabilization: The implicit bias of gradient descent at the edge of stability

Reference 58

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source=pdf_text observed=2026-08-06T00:43:09.201807Z digest=sha256:f216de464d7a933bb38b2fda5bf1186a3cb35b7d3bc0637cee9248a8184cd884

Observation a3d98e78-a06c-4464-8bea-602aa2e4e2df · outbound

This paper cites Robust Linear Regression: Phase-Transitions and Precise Tradeoffs for General Norms.

The Fourth Quadrant: A Stylized View of Benign Misfitting Robust Linear Regression: Phase-Transitions and Precise Tradeoffs for General Norms

Reference 59

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local_arxiv, observed 2026-08-06T00:43:27.789618Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T00:43:09.842066Z digest=sha256:36b3a3165c38055201f7d3c68083313ae91bb7831b471f0766fa54619a10697b

Observation 4d40ae35-6dee-4ec1-b63f-a20d18475cdf · outbound

This paper cites Draper and R.

The Fourth Quadrant: A Stylized View of Benign Misfitting Draper and R

Reference 60

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source=pdf_text observed=2026-08-06T00:43:09.886688Z digest=sha256:25f14388dd3e5fe474bc07c12574322b3f49c1c7f441eca65f422e8ea3761ad4

Observation 042e113e-796a-472e-8b42-d58da616b758 · outbound

This paper cites Learning single-index models in gaussian space.

The Fourth Quadrant: A Stylized View of Benign Misfitting Learning single-index models in gaussian space

Reference 61

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source=pdf_text observed=2026-08-06T00:43:09.982201Z digest=sha256:b5fcfd1678f06544176757ba30a8ce7d08c3c14a345373f8477be698c0dbe32c

Observation 4e03b9ad-665e-47f5-8b88-b725ec552ec1 · outbound

This paper cites The algorithmic foundations of differential privacy.

The Fourth Quadrant: A Stylized View of Benign Misfitting The algorithmic foundations of differential privacy

Reference 62

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source=pdf_text observed=2026-08-06T00:43:10.073706Z digest=sha256:956cbc55ecebb4bf0fddfd1e45aecec78da2cc588fd09150e49f387656b29516

Observation 75d2b213-374e-49f0-b815-a0bb736273f3 · outbound

This paper cites Generalized no free lunch theorem for adversarial robustness.

The Fourth Quadrant: A Stylized View of Benign Misfitting Generalized no free lunch theorem for adversarial robustness

Reference 63

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source=pdf_text observed=2026-08-06T00:43:09.755729Z digest=sha256:aeaaa9ade883a76b52b32407364dddee34d0b29f3d82a8ab0ae5957d38107f25

Observation 425dfae3-3119-4430-9eae-8ffa897b9f36 · outbound

This paper cites Analyze gauss: Optimal bounds for privacy-preserving principal component analysis.

The Fourth Quadrant: A Stylized View of Benign Misfitting Analyze gauss: Optimal bounds for privacy-preserving principal component analysis

Reference 64

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source=pdf_text observed=2026-08-06T00:43:10.261659Z digest=sha256:3501716f3a537715b8c86f7fb9bec33034a47427c1bab642c26c67e089fb7a2b

Observation ce0d6bdb-5910-44f1-b113-2aeaf4d563a7 · outbound

This paper cites James–stein estimation and ridge regression.

The Fourth Quadrant: A Stylized View of Benign Misfitting James–stein estimation and ridge regression

Reference 65

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no resolver link, observed 2026-08-06T00:43:10.314624Z

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source=pdf_text observed=2026-08-06T00:43:10.314624Z digest=sha256:0334c541343def5079d41b640e0956a4e61d9dd386b2e132c09dfdacbd143ea4

Observation 95e97e02-c1f0-4131-80d8-9252d11c570e · outbound

This paper cites Stein’s paradox in statistics.Scientific American, 236(5): 119–127, 1977.

The Fourth Quadrant: A Stylized View of Benign Misfitting Stein’s paradox in statistics.Scientific American, 236(5): 119–127, 1977

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T00:43:10.374818Z digest=sha256:d7d81af6b5e4215ac5da534a17430c838c5e5629963086baece865cc0434c383

Observation 460f1392-bc51-49ab-86e5-c322ae8c0694 · outbound

This paper cites Etkin, David N.

The Fourth Quadrant: A Stylized View of Benign Misfitting Etkin, David N

Reference 67

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metadata mismatch
raw_fallback, observed 2026-08-06T00:43:27.551876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T00:43:10.453490Z digest=sha256:f6b2a69fb2d241b15a885fbcfc65de5b0e18e4f3b3f7c84d9ab48bc214abe8b4

Observation 5842c1ec-1cfd-4446-9635-211e40c08eeb · outbound

This paper cites Calibrating noise to sensitivity in private data analysis.

The Fourth Quadrant: A Stylized View of Benign Misfitting Calibrating noise to sensitivity in private data analysis

Reference 68

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source=pdf_text observed=2026-08-06T00:43:10.173656Z digest=sha256:2bcde51189daf4ca22eb0617ae16968d08a1dbd10eca77ba509d67c49e605c7d

Observation 7c784198-c46a-4eca-b2c1-75166fd0d2d6 · outbound

This paper cites Analysis of classifiers’ robustness to adversarial perturbations.Machine Learning, 107:481–508, 2018.

The Fourth Quadrant: A Stylized View of Benign Misfitting Analysis of classifiers’ robustness to adversarial perturbations.Machine Learning, 107:481–508, 2018

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source=pdf_text observed=2026-08-06T00:43:10.570826Z digest=sha256:6dbd059e91c1d2f9a27189c01121f9221714b79d9256e97b93dbc4ffdae097b9

Observation 4727e863-adc9-4054-a65e-cdd590dec05e · outbound

This paper cites Generalization of ERM in stochastic convex optimization: The dimension strikes back.

The Fourth Quadrant: A Stylized View of Benign Misfitting Generalization of ERM in stochastic convex optimization: The dimension strikes back

Reference 70

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source=pdf_text observed=2026-08-06T00:43:10.703933Z digest=sha256:bf28065f4c3de25e5c75500f7811722c907e66bd782de126cb734a48fe816bc0

Observation 9817b1ee-6454-4376-9ffc-6e0cfc3480ab · outbound

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

The Fourth Quadrant: A Stylized View of Benign Misfitting Does learning require memorization? a short tale about a long tail

Reference 71

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no resolver link, observed 2026-08-06T00:43:10.765272Z

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source=pdf_text observed=2026-08-06T00:43:10.765272Z digest=sha256:7f7c6d905b8e5813c3e24e6e68a1ce602324c77a90dd9144f10ac6c33c5b259a

Observation 63d2f1c7-dc46-44f2-90b9-a31559d5f415 · outbound

This paper cites Figiel, J.

The Fourth Quadrant: A Stylized View of Benign Misfitting Figiel, J

Reference 72

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source=pdf_text observed=2026-08-06T00:43:10.848008Z digest=sha256:25d43c1b295c34cb932a7def32b72fee620f0bd3281804d9c168561f92af5570

Observation 123e1ae9-a603-4d37-b676-fb68069507c9 · outbound

This paper cites (S)GD over diagonal linear networks: Implicit bias, large stepsizes and edge of stability.

The Fourth Quadrant: A Stylized View of Benign Misfitting (S)GD over diagonal linear networks: Implicit bias, large stepsizes and edge of stability

Reference 73

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source=pdf_text observed=2026-08-06T00:43:10.497754Z digest=sha256:99a522a45ca57b780aa6eb6e1367856a822babb474ad320d439015e46c4c9f43

Observation 83456e24-5c47-4dec-b8cc-c1078e855b4a · outbound

This paper cites Shrinkage to Infinity: Reducing Test Error by Inflating the Minimum Norm Interpolator in Linear Models.

The Fourth Quadrant: A Stylized View of Benign Misfitting Shrinkage to Infinity: Reducing Test Error by Inflating the Minimum Norm Interpolator in Linear Models

Reference 74

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local_arxiv, observed 2026-08-06T00:43:27.210374Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T00:43:11.009537Z digest=sha256:a1799631c9d003086022183357ac2bb98a4c4c9fd2c75093ec970f85bad803fb

Observation 80ba0f8b-41bd-432d-af88-68693e1b901e · outbound

This paper cites Bartlett, and Nati Srebro.

The Fourth Quadrant: A Stylized View of Benign Misfitting Bartlett, and Nati Srebro

Reference 75

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source=pdf_text observed=2026-08-06T00:43:11.094005Z digest=sha256:0a4b7b8f17481569772777086f0b1072547f793255e2c4f42f2d9faf9d4549b1

Observation c709d151-9d79-40c3-ab97-bd28d30128f9 · outbound

This paper cites Gallager.Information Theory and Reliable Communication.

The Fourth Quadrant: A Stylized View of Benign Misfitting Gallager.Information Theory and Reliable Communication

Reference 76

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source=pdf_text observed=2026-08-06T00:43:11.183312Z digest=sha256:c614ceb7c6559ae1e37426ab0461aa435c06a6f2eeac8f9b0ae8f8154787ce40

Observation d075e37e-99dd-4de3-bf1f-51665d7e6508 · outbound

This paper cites Escaping from saddle points—online stochastic gradient for tensor decomposition.

The Fourth Quadrant: A Stylized View of Benign Misfitting Escaping from saddle points—online stochastic gradient for tensor decomposition

Reference 77

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source=pdf_text observed=2026-08-06T00:43:11.308150Z digest=sha256:a7c645f3a4bba1f834cc823ffd1eeb44dd0b8251331c4fc68b4ddbc00bee0610

Observation c1712fa0-d309-415c-b303-bb4624770ae5 · outbound

This paper cites Foster, Satyen Kale, Haipeng Luo, Mehryar Mohri, and Karthik Sridharan.

The Fourth Quadrant: A Stylized View of Benign Misfitting Foster, Satyen Kale, Haipeng Luo, Mehryar Mohri, and Karthik Sridharan

Reference 78

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no resolver link, observed 2026-08-06T00:43:10.911969Z

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source=pdf_text observed=2026-08-06T00:43:10.911969Z digest=sha256:0336be45254ffea211c23da94e876f317c5c7e93b966188df272fc584c163818

Observation ef560da2-942a-4dc2-846f-5412a129e83c · outbound

This paper cites A loss curvature perspective on training instabilities of deep learning models.

The Fourth Quadrant: A Stylized View of Benign Misfitting A loss curvature perspective on training instabilities of deep learning models

Reference 79

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source=pdf_text observed=2026-08-06T00:43:11.489977Z digest=sha256:876d7b56cd557a4f335fcd5ff4a4649934b3f17248bd912756e4dd982c0412cb

Observation c009c686-e56d-444b-ab21-a39c99b50891 · outbound

This paper cites Goodfellow, Jonathon Shlens, and Christian Szegedy.

The Fourth Quadrant: A Stylized View of Benign Misfitting Goodfellow, Jonathon Shlens, and Christian Szegedy

Reference 80

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no resolver link, observed 2026-08-06T00:43:11.571088Z

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source=pdf_text observed=2026-08-06T00:43:11.571088Z digest=sha256:7915f8105f2ffcbae60d8a510e7af0351f15e68fa92c192835c43ca469510a18

Observation fc4c62f5-9f12-42bd-8267-2a156f8b84a5 · outbound

This paper cites Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour.

The Fourth Quadrant: A Stylized View of Benign Misfitting Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour

Reference 81

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source=pdf_text observed=2026-08-06T00:43:11.696995Z digest=sha256:35b94bd7d42f1ab9814d12590dfd382cd855ee985f387b5cbbd52db1f964f2cc

Observation 629a6ae9-406f-4ce2-90fe-def2a8e2bbbc · outbound

This paper cites Characterizing implicit bias in terms of optimization geometry.

The Fourth Quadrant: A Stylized View of Benign Misfitting Characterizing implicit bias in terms of optimization geometry

Reference 82

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no resolver link, observed 2026-08-06T00:43:11.748676Z

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source=pdf_text observed=2026-08-06T00:43:11.748676Z digest=sha256:ca1744edb865932649f84fbb0e70f797cad6e1659597d486d31bb37f194df561

Observation 49344df1-cfdf-4c49-b5e6-2178187498eb · outbound

This paper cites Schoenholz, Maithra Raghu, Martin Wattenberg, and Ian Goodfellow.

The Fourth Quadrant: A Stylized View of Benign Misfitting Schoenholz, Maithra Raghu, Martin Wattenberg, and Ian Goodfellow

Reference 83

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source=pdf_text observed=2026-08-06T00:43:11.423047Z digest=sha256:20f312704819eac104d0692180bc97cd3498ef83c838bb17b53e5a7a94e5e039

Observation ba478612-3702-459e-abce-7de023429f0f · outbound

This paper cites The Surprising Harmfulness of Benign Overfitting for Adversarial Robustness.

The Fourth Quadrant: A Stylized View of Benign Misfitting The Surprising Harmfulness of Benign Overfitting for Adversarial Robustness

Reference 84

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source=pdf_text observed=2026-08-06T00:43:11.892432Z digest=sha256:363b82e6c5b22bbc077f0fac79ccee6be0339423222ef3673a7624e0205568ea

Observation 5474ec28-c1f9-4c89-a7b9-f1987bb11d50 · outbound

This paper cites HaoChen, Colin Wei, Jason D.

The Fourth Quadrant: A Stylized View of Benign Misfitting HaoChen, Colin Wei, Jason D

Reference 85

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source=pdf_text observed=2026-08-06T00:43:11.991022Z digest=sha256:deb57c0aa792b7de1c8b0ab567044f8b828510f556193a50dbc115639e7db286

Observation 2e06514e-79b0-45b5-893b-01d1fd2f2d43 · outbound

This paper cites On the geometry of differential privacy.

The Fourth Quadrant: A Stylized View of Benign Misfitting On the geometry of differential privacy

Reference 86

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source=pdf_text observed=2026-08-06T00:43:12.085416Z digest=sha256:63dceca87530cfa0ff208d47b187111acd3299f05555b44d7d0bfd44619d9db1

Observation 9eabd5b3-cdc9-4c59-81fd-ffac3f73d507 · outbound

This paper cites Train faster, generalize better: Stability of stochastic gradient descent.

The Fourth Quadrant: A Stylized View of Benign Misfitting Train faster, generalize better: Stability of stochastic gradient descent

Reference 87

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source=pdf_text observed=2026-08-06T00:43:12.187276Z digest=sha256:1842eba33dd18bae653a922bebce3d5896dd8c713bfe1fe7ce426ee45d6758f1

Observation f6cc8814-410b-4779-9d53-55fa78d2d845 · outbound

This paper cites The optimal sample complexity of PAC learning.Journal of Machine Learning Research, 17(38):1–15, 2016.

The Fourth Quadrant: A Stylized View of Benign Misfitting The optimal sample complexity of PAC learning.Journal of Machine Learning Research, 17(38):1–15, 2016

Reference 88

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no resolver link, observed 2026-08-06T00:43:11.808949Z

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source=pdf_text observed=2026-08-06T00:43:11.808949Z digest=sha256:2f2162e0c934d7a942040899e41401ef1b867ad89290cf2f3474d93e8d2383e6

Observation 0dcb719a-d747-44b2-b146-f1a488686726 · outbound

This paper cites Tibshirani.

The Fourth Quadrant: A Stylized View of Benign Misfitting Tibshirani

Reference 89

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source=pdf_text observed=2026-08-06T00:43:12.404742Z digest=sha256:914ed78eca830e8d71982c3c6c3ab4892424e72b8640497ea7d8b065d9ec285e

Observation f8547bd8-49a5-4b90-ad19-77388ed061b5 · outbound

This paper cites Herman.Fundamentals of Computerized Tomography: Image Reconstruction from Projections.

The Fourth Quadrant: A Stylized View of Benign Misfitting Herman.Fundamentals of Computerized Tomography: Image Reconstruction from Projections

Reference 90

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source=pdf_text observed=2026-08-06T00:43:12.643811Z digest=sha256:4fca83bbb6c59492336147ad8a244c6a2e83c68a3d50e1ba229654b055de045b

Observation 6861211d-d147-4fa8-acad-d64f3f94f3c4 · outbound

This paper cites Flat minima.Neural Computation, 9(1):1–42, 1997.

The Fourth Quadrant: A Stylized View of Benign Misfitting Flat minima.Neural Computation, 9(1):1–42, 1997

Reference 91

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source=pdf_text observed=2026-08-06T00:43:12.740159Z digest=sha256:4b0c14d7de012a85422c276993b7bd18ba6e652034a652748487abe50ada752b

Observation 4ffac5ef-f471-462b-b208-aea5c20791e6 · outbound

This paper cites Euclidean information theory of networks.

The Fourth Quadrant: A Stylized View of Benign Misfitting Euclidean information theory of networks

Reference 92

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source=pdf_text observed=2026-08-06T00:43:12.817561Z digest=sha256:18c223b09048f4dfca2a611cbc8cc43866df7f8f6e2c46c19bc027c7f0880e54

Observation 8910bdab-3b37-4ab4-8d2c-896f3405fca7 · outbound

This paper cites Hochwald.

The Fourth Quadrant: A Stylized View of Benign Misfitting Hochwald

Reference 93

Resolution
malformed identifier
raw_fallback, observed 2026-08-06T00:43:26.842342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T00:43:12.289363Z digest=sha256:51a658335205c3f2c97c26ecf3d5b131ad2329dd4401103b3cd8212f0f4293d8

Observation 3b8059b7-1722-4d83-a3ef-1cfff72c9bd1 · outbound

This paper cites Optimizer dynamics at the edge of stability with differential privacy, 2025.

The Fourth Quadrant: A Stylized View of Benign Misfitting Optimizer dynamics at the edge of stability with differential privacy, 2025

Reference 94

Resolution
verified exact
raw_fallback, observed 2026-08-06T00:43:26.509220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T00:43:13.011392Z digest=sha256:9a6ae90bed64f81db5f8edbe39f39bfbe819811750b6b759cbc9fd01941f945c

Observation a4bca984-bb6f-496e-95ee-29905325a919 · outbound

This paper cites Adversarial examples are not bugs, they are features.

The Fourth Quadrant: A Stylized View of Benign Misfitting Adversarial examples are not bugs, they are features

Reference 95

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source=pdf_text observed=2026-08-06T00:43:13.117442Z digest=sha256:caf232b6d508ac2dc9e5562f86801d6b6f61f6dea2bed0f9d61c65d0062d9352

Observation 7df306f3-ffcb-4133-96ce-ba22b247e6c4 · outbound

This paper cites Kakade, Rahul Kidambi, Praneeth Netrapalli, and Aaron Sidford.

The Fourth Quadrant: A Stylized View of Benign Misfitting Kakade, Rahul Kidambi, Praneeth Netrapalli, and Aaron Sidford

Reference 96

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source=pdf_text observed=2026-08-06T00:43:13.203394Z digest=sha256:dd0802ac3165631b75f89a876407182e34014a7c1ce3b4742470ca584e9f1359

Observation d81465bb-9066-41d8-a960-6efb982f71b1 · outbound

This paper cites James and Charles Stein.

The Fourth Quadrant: A Stylized View of Benign Misfitting James and Charles Stein

Reference 97

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source=pdf_text observed=2026-08-06T00:43:13.290828Z digest=sha256:1a07fff41c33636fbf3332876d56a55b099d3a6d2862b64b14e74d0427a02555

Observation 1a41e5de-bb95-4aea-8691-02e5f0fe6acd · outbound

This paper cites Three Factors Influencing Minima in SGD.

The Fourth Quadrant: A Stylized View of Benign Misfitting Three Factors Influencing Minima in SGD

Reference 98

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source=pdf_text observed=2026-08-06T00:43:13.366129Z digest=sha256:b1a19eaae475f7f0cc26ee8866e0d7551d62323f33064ceb2d76299daa7928dd

Observation 3f6b1769-b5f6-4165-ae79-a277d051fc70 · outbound

This paper cites Wornell, and Lizhong Zheng.

The Fourth Quadrant: A Stylized View of Benign Misfitting Wornell, and Lizhong Zheng

Reference 99

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verified exact
doi, observed 2026-08-06T00:43:24.014747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T00:43:12.902603Z digest=sha256:2f023300c9a0fbf9447060e08ee4f8df2819ad44a3d098c327eb46f50542e885

Observation 64f44887-eada-4427-ac04-209856775d76 · outbound

This paper cites Jerrum, Leslie G.

The Fourth Quadrant: A Stylized View of Benign Misfitting Jerrum, Leslie G

Reference 100

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source=pdf_text observed=2026-08-06T00:43:13.551631Z digest=sha256:0371789d22673a01241572faa08f3ed48a221150a63ae6f1586190981b255854

Pith citing papers

No inbound Pith citation observations are available.