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Paper Citation Record · LEDGER

Double Descent Demystified: Identifying, Interpreting & Ablating the Sources of a Deep Learning Puzzle

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2303.14151.

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

pith.paper-citation-record.v1
2303.14151 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:54:27.953376Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T01:05:16.054809Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation f617f965-0af7-470c-a96f-6f1327b70169 · inbound

Path Regularization: A Near-Complete and Optimal Nonasymptotic Generalization Theory for Multilayer Neural Networks and Double Descent Phenomenon cites this paper.

Path Regularization: A Near-Complete and Optimal Nonasymptotic Generalization Theory for Multilayer Neural Networks and Double Descent Phenomenon Double Descent Demystified: Identifying, Interpreting & Ablating the Sources of a Deep Learning Puzzle

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-23T01:05:16.058417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-23T01:03:39.897679Z digest=sha256:3ce82899ee2bab9f7dd109bb5422e4ad6a6dbcac60a6ba28f7d60648372453ac

Observation be9a9ef2-2038-4cbc-9e16-ce952066c6e7 · inbound

Approach to Finding a Robust Deep Learning Model cites this paper.

Approach to Finding a Robust Deep Learning Model Double Descent Demystified: Identifying, Interpreting & Ablating the Sources of a Deep Learning Puzzle

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-07T14:54:27.953376Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:54:27.953376Z digest=sha256:8052aaab7b87e80b685039fc71010d2b22563129a52f6188554a5acce6572526

Observation 9c24ee91-2564-4051-a5bf-42ea1d95baa0 · inbound

Black hole/quantum machine learning correspondence cites this paper.

Black hole/quantum machine learning correspondence Double Descent Demystified: Identifying, Interpreting & Ablating the Sources of a Deep Learning Puzzle

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-07T04:48:09.511400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:48:09.511400Z digest=sha256:9b6ebbbba2fa997da1ba686140254969e04a02407b1e7ae7760de1b8cb3d7dc4

Observation 3262dbd5-e792-49f1-ae86-202ab574f0b0 · inbound

Large Language Models and Emergence: A Complex Systems Perspective cites this paper.

Large Language Models and Emergence: A Complex Systems Perspective Double Descent Demystified: Identifying, Interpreting & Ablating the Sources of a Deep Learning Puzzle

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-07T04:57:40.657662Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:57:40.657662Z digest=sha256:c9f2c98bcc2cd17f269d5f352bd989877ad0ac7baf0a6b7b17819e28594f9a93

Observation e525b1a0-8450-4960-9ba0-53acafc27380 · inbound

Deep learning inference with the Event Horizon Telescope II. The Zingularity framework for Bayesian artificial neural networks cites this paper.

Deep learning inference with the Event Horizon Telescope II. The Zingularity framework for Bayesian artificial neural networks Double Descent Demystified: Identifying, Interpreting & Ablating the Sources of a Deep Learning Puzzle

Reference 182

Resolution
unresolved
no resolver link, observed 2026-08-07T00:33:58.614910Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:33:58.614910Z digest=sha256:3314f87f9e3293b55d34c445b1117ca40910a925c25431508b91770504a8432f

Observation d296b0dc-ecdb-4715-a6a7-7591776ba159 · inbound

Double Descent in Quantum Kernel Ridge Regression cites this paper.

Double Descent in Quantum Kernel Ridge Regression Double Descent Demystified: Identifying, Interpreting & Ablating the Sources of a Deep Learning Puzzle

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-10T06:46:37.388895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-10T06:42:30.100063Z digest=sha256:bbbd5381cba9c5d52330866b0a2f4825dbfcccbb46ade37ab97876ba8b59e377

Observation bf9559dc-08bd-478f-a426-fe23e130905d · inbound

How Much is Brain Data Worth for Machine Learning? cites this paper.

How Much is Brain Data Worth for Machine Learning? Double Descent Demystified: Identifying, Interpreting & Ablating the Sources of a Deep Learning Puzzle

Reference 33

Resolution
verified exact
arxiv_id, observed 2026-05-12T06:41:45.730308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-12T04:01:28.080306Z digest=sha256:e2215a711f0e10201ed42463fed563a358e7fd7428e8f81f08fe37aad1b7f085