Paper Citation Record · LEDGER

Optimal Regularization Can Mitigate Double Descent

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2003.01897.

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

pith.paper-citation-record.v1
2003.01897 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T06:03:00.601341Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

48
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 2f6ef4e8-bd5f-4d7c-ae12-595303d66d7a · inbound

Quantifying the Prediction Uncertainty of Machine Learning Models for Individual Data cites this paper.

Quantifying the Prediction Uncertainty of Machine Learning Models for Individual Data Optimal Regularization Can Mitigate Double Descent

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-11T18:53:10.365287Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab2b6936-ca4d-4deb-8f71-96921cb459f2 · inbound

The Double Descent Behavior in Two Layer Neural Network for Binary Classification cites this paper.

The Double Descent Behavior in Two Layer Neural Network for Binary Classification Optimal Regularization Can Mitigate Double Descent

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-16T06:03:00.601341Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b4979844-d73d-4a96-abf7-481c6f40a148 · inbound

Pre-trained Large Language Models Learn Hidden Markov Models In-context cites this paper.

Pre-trained Large Language Models Learn Hidden Markov Models In-context Optimal Regularization Can Mitigate Double Descent

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-19T10:37:15.052151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c849ba4f-fc9c-4505-ac4c-57efd31bdf55 · inbound

A Ridge Too Far: Correcting Over-Shrinkage via Negative Regularization cites this paper.

A Ridge Too Far: Correcting Over-Shrinkage via Negative Regularization Optimal Regularization Can Mitigate Double Descent

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-05-18T21:01:50.908680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4405f323-b7b7-4708-b1cd-e2b0a1ff6a63 · inbound

Double Descent in Quantum Kernel Ridge Regression cites this paper.

Double Descent in Quantum Kernel Ridge Regression Optimal Regularization Can Mitigate Double Descent

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-10T06:46:37.376896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c53bbe3c-16f0-40ae-a679-4f3b2c094fda · inbound

Unveiling Memorization-Generalization Coexistence: A Case Study on Arithmetic Tasks with Label Noise cites this paper.

Unveiling Memorization-Generalization Coexistence: A Case Study on Arithmetic Tasks with Label Noise Optimal Regularization Can Mitigate Double Descent

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-20T12:28:16.629714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 958f3099-5cf2-482f-b92f-b0eab4984241 · inbound

A Theory on Flow Matching with Neural Networks cites this paper.

A Theory on Flow Matching with Neural Networks Optimal Regularization Can Mitigate Double Descent

Reference 36

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T00:47:30.918048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d1670583-2b7c-42f1-84bc-4fd1765230b1 · inbound

Explaining Machine Learning and Memorization with Statistical Mechanics cites this paper.

Explaining Machine Learning and Memorization with Statistical Mechanics Optimal Regularization Can Mitigate Double Descent

Reference 162

Resolution: verified exact; arxiv_id, observed 2026-07-01T06:05:28.869760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c050cc65-6988-462d-973b-07f9fe98b947 · inbound

Domain Adaptation of Mismatched Proximal Denoiser for Plug-and-Play Image Reconstruction cites this paper.

Domain Adaptation of Mismatched Proximal Denoiser for Plug-and-Play Image Reconstruction Optimal Regularization Can Mitigate Double Descent

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-02T00:50:35.581710Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.