Paper Citation Record · LEDGER

Prevalence of Neural Collapse during the terminal phase of deep learning training

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2008.08186.

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

pith.paper-citation-record.v1
2008.08186 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T14:17:37.183370Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T04:17:36.694526Z

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 1c767e82-b8fc-40e7-bc92-e3eed480adf3 · inbound

Feature learning is decoupled from generalization in high capacity neural networks cites this paper.

Feature learning is decoupled from generalization in high capacity neural networks Prevalence of Neural Collapse during the terminal phase of deep learning training

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-06T14:17:37.183370Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c1979af-c309-4969-8f54-4c2f1decec25 · inbound

ILDR: Geometric Early Detection of Grokking cites this paper.

ILDR: Geometric Early Detection of Grokking Prevalence of Neural Collapse during the terminal phase of deep learning training

Reference 6

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T13:36:09.158173Z

Source-reported events for the cited work

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

Observation 2daf136d-7912-4068-aa48-53e38363f176 · inbound

Where Pretraining writes and Alignment reads: the asymmetry of Transformer weight space cites this paper.

Where Pretraining writes and Alignment reads: the asymmetry of Transformer weight space Prevalence of Neural Collapse during the terminal phase of deep learning training

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-20T20:39:00.230372Z

Source-reported events for the cited work

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

Observation 89008702-4d8d-4253-b9a3-8f34a68a0e6e · inbound

Learning from almost nothing: How neural networks survive heavy input corruption cites this paper.

Learning from almost nothing: How neural networks survive heavy input corruption Prevalence of Neural Collapse during the terminal phase of deep learning training

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-07-03T04:17:36.696242Z

Source-reported events for the cited work

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

Observation 94e5bdc8-dde7-486e-ba02-55d4e919b4ed · inbound

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization cites this paper.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Prevalence of Neural Collapse during the terminal phase of deep learning training

Reference 39

Resolution: unresolved; no resolver link, observed 2026-07-14T09:21:21.442535Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a0eb7caf-cc62-4180-88c0-23bef0162bbb · inbound

CoCaRS: Correlation Calibration-Based Redundancy Suppression for Heterogeneous Knowledge Distillation cites this paper.

CoCaRS: Correlation Calibration-Based Redundancy Suppression for Heterogeneous Knowledge Distillation Prevalence of Neural Collapse during the terminal phase of deep learning training

Reference 26

Resolution: unresolved; no resolver link, observed 2026-07-30T12:36:02.226489Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.