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Paper Citation Record · LEDGER

Neural Collapse: A Review on Modelling Principles and Generalization

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2206.04041.

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

pith.paper-citation-record.v1
2206.04041 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:30:49.906797Z

measured 1 of 1 external citation measurements

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

Source: pith, 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

12
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 2a48d8ac-ed95-4afc-9510-904fa43b91f4 · inbound

Superposition Yields Robust Neural Scaling cites this paper.

Superposition Yields Robust Neural Scaling Neural Collapse: A Review on Modelling Principles and Generalization

Reference 38

Resolution
metadata mismatch
arxiv_id, observed 2026-05-09T06:36:25.580041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-22T14:38:44.789822Z digest=sha256:3bd42ebaccf247def9eb1a40422d69dcf3911586e92bbfade4389b1efc290b50

Observation 3487a408-09a7-4115-bd16-98eafa94599d · inbound

Open-Set Semi-Supervised Learning for Long-Tailed Medical Datasets cites this paper.

Open-Set Semi-Supervised Learning for Long-Tailed Medical Datasets Neural Collapse: A Review on Modelling Principles and Generalization

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T15:30:49.906797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:30:49.906797Z digest=sha256:0d9732d47893f9c3fd629782a190d04e93f639dde169f6c065c77fb53b64bd37

Observation 950a49b5-cdf4-445e-8e06-ded169d96f66 · inbound

The Features at Convergence Theorem: a first-principles alternative to the Neural Feature Ansatz for how networks learn representations cites this paper.

The Features at Convergence Theorem: a first-principles alternative to the Neural Feature Ansatz for how networks learn representations Neural Collapse: A Review on Modelling Principles and Generalization

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-06T19:31:20.976793Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:31:20.976793Z digest=sha256:16b3f2fd445ee23ecc3446cba6aca476c958a51a564d76274043b967593d3152

Observation f97d82b0-a8d7-4014-9b2c-1eaff7091f5e · inbound

FedWCM: Unleashing the Potential of Momentum-based Federated Learning in Long-Tailed Scenarios cites this paper.

FedWCM: Unleashing the Potential of Momentum-based Federated Learning in Long-Tailed Scenarios Neural Collapse: A Review on Modelling Principles and Generalization

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-06T15:49:06.687319Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:49:06.687319Z digest=sha256:c5adc2598487b486b84143947db51dc8c10a9ac43c07059291f69f294a922333

Observation f0e1369d-40ec-478c-82bf-94d7d5869042 · 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 Neural Collapse: A Review on Modelling Principles and Generalization

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-06T14:17:37.133481Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:17:37.133481Z digest=sha256:1ef1aa0415a882d0f38e4db8bf80d088340ec63b321e4f879a8d549268ca7b1c

Observation d83254de-0cfb-4133-bc54-24991b8a0789 · inbound

There Will Be a Scientific Theory of Deep Learning cites this paper.

There Will Be a Scientific Theory of Deep Learning Neural Collapse: A Review on Modelling Principles and Generalization

Reference 80

Resolution
verified exact
arxiv_id, observed 2026-05-11T15:21:08.656048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-09T20:11:17.616190Z digest=sha256:c39ce1425d0029e60592395e3ceb238d9a4d3a442afe0d0da89c1758f1417aef

Observation 0406925d-959f-40ff-bd23-6e767b6c2fe8 · inbound

How Label Imbalance Shapes Geometry: A General Spectral Analysis of Multi-Label Neural Collapse cites this paper.

How Label Imbalance Shapes Geometry: A General Spectral Analysis of Multi-Label Neural Collapse Neural Collapse: A Review on Modelling Principles and Generalization

Reference 48

Resolution
verified exact
arxiv_id, observed 2026-05-08T19:34:04.858825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-08T19:29:49.018621Z digest=sha256:d1238f1a5ee293fccdfdef7ee8b936dd2cbcc62983bd7d47f89eac97c909e5fd

Observation 4c24e092-5964-4154-86fe-835946959f55 · inbound

Manifold-Constrained Adversarial Training for Long-Tailed Robustness via Geometric Alignment cites this paper.

Manifold-Constrained Adversarial Training for Long-Tailed Robustness via Geometric Alignment Neural Collapse: A Review on Modelling Principles and Generalization

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-09T06:05:34.765302Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-08T19:02:26.047252Z digest=sha256:b21a93555493d400930ecee31fc7f9e5a6974bb9a81a1474fe6082952c56f0f0

Observation a181cd52-a30c-44a6-8529-1b1abae5c447 · inbound

Optimal Representations for Generalized Contrastive Learning with Imbalanced Datasets cites this paper.

Optimal Representations for Generalized Contrastive Learning with Imbalanced Datasets Neural Collapse: A Review on Modelling Principles and Generalization

Reference 59

Resolution
verified exact
arxiv_id, observed 2026-05-13T02:32:06.168537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-13T02:31:56.483055Z digest=sha256:d7e198220d3762aaabb6af0f46e909b6230a0a3cb6c522a9f4979cfe2715ac4e

Observation 476a716f-d74e-4b77-8105-aee9f88d1301 · 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 Neural Collapse: A Review on Modelling Principles and Generalization

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-07-03T04:17:36.696557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-27T14:06:36.969337Z digest=sha256:441fa83516dddbdf971a7aedf0bad09c9834cf004c3775ddc84859b2f6f72406

Observation 87a09b96-cfcb-4a85-aac0-c6884f9b567b · inbound

Two-Stage Multi-Modal Fusion with Adaptive Alignment for Action Quality Assessment cites this paper.

Two-Stage Multi-Modal Fusion with Adaptive Alignment for Action Quality Assessment Neural Collapse: A Review on Modelling Principles and Generalization

Reference 2

Resolution
verified exact
local_arxiv, observed 2026-07-09T11:16:11.444678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-07-09T11:08:15.865799Z digest=sha256:c35a4433d353577c818fe47b608a4189b5b6fb5f90a26412ce0117b4fd7e812b

Observation 62f82a29-a10f-4a1e-965f-79ea3ef81ab2 · inbound

How to Tame Grokking: Representation Geometry as a Control Signal cites this paper.

How to Tame Grokking: Representation Geometry as a Control Signal Neural Collapse: A Review on Modelling Principles and Generalization

Reference 12

Resolution
unresolved
no resolver link, observed 2026-07-14T04:01:12.361370Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T04:01:12.361370Z digest=sha256:aa50a6aa307eda3b819371eff3567ba836a1c06b8630e9c6fa155634aae1aad8