Paper Citation Record · LEDGER

Neural Mechanics: Symmetry and Broken Conservation Laws in Deep Learning Dynamics

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2012.04728.

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

pith.paper-citation-record.v1
2012.04728 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T06:06:57.442994Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T04:27:36.920358Z

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 65df48c7-5d0f-4e6a-a05b-84f11d2b151a · inbound

TeleSparse: Practical Privacy-Preserving Verification of Deep Neural Networks cites this paper.

TeleSparse: Practical Privacy-Preserving Verification of Deep Neural Networks Neural Mechanics: Symmetry and Broken Conservation Laws in Deep Learning Dynamics

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-16T06:06:57.442994Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 93e00a5b-96c1-4402-a5f7-04cb1c2cb686 · inbound

Toward Manifest Relationality in Transformers via Symmetry Reduction cites this paper.

Toward Manifest Relationality in Transformers via Symmetry Reduction Neural Mechanics: Symmetry and Broken Conservation Laws in Deep Learning Dynamics

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-02T21:52:35.416538Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17ce661d-991a-49f7-bbf9-e0aeb971c053 · inbound

A Theory of Saddle Escape in Deep Nonlinear Networks cites this paper.

A Theory of Saddle Escape in Deep Nonlinear Networks Neural Mechanics: Symmetry and Broken Conservation Laws in Deep Learning Dynamics

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:51:05.717524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b12013a8-6950-4565-aaeb-ee34d7e703c7 · inbound

A Theory of Saddle Escape in Deep Nonlinear Networks cites this paper.

A Theory of Saddle Escape in Deep Nonlinear Networks Neural Mechanics: Symmetry and Broken Conservation Laws in Deep Learning Dynamics

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-11T02:25:54.510205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4c8d2ccd-53fa-4f53-8129-ac2a3b3831a8 · inbound

A Theory of Saddle Escape in Deep Nonlinear Networks cites this paper.

A Theory of Saddle Escape in Deep Nonlinear Networks Neural Mechanics: Symmetry and Broken Conservation Laws in Deep Learning Dynamics

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-07-01T00:45:12.007531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 806b4588-7239-43d2-b5b3-0b18ee09f4e8 · inbound

Learning reveals invisible structure in low-rank RNNs cites this paper.

Learning reveals invisible structure in low-rank RNNs Neural Mechanics: Symmetry and Broken Conservation Laws in Deep Learning Dynamics

Reference 50

Resolution: metadata mismatch; arxiv_id, observed 2026-05-09T06:15:39.625604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 15937e6f-3936-4566-bfb7-14e57a82d55f · inbound

SOLAR: A Self-Optimizing Open-Ended Autonomous Agent for Lifelong Learning and Continual Adaptation cites this paper.

SOLAR: A Self-Optimizing Open-Ended Autonomous Agent for Lifelong Learning and Continual Adaptation Neural Mechanics: Symmetry and Broken Conservation Laws in Deep Learning Dynamics

Reference 44

Resolution: verified exact; arxiv_id, observed 2026-05-21T11:24:08.626851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d312d5a4-ceb6-4458-91dd-0aed16155d1c · inbound

Dead Directions: Geometric Singular Learning cites this paper.

Dead Directions: Geometric Singular Learning Neural Mechanics: Symmetry and Broken Conservation Laws in Deep Learning Dynamics

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-07-02T11:36:55.214326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation fe9ba437-3ea4-4217-9cdb-3cee0a70641f · inbound

Second-Order Path Kernel Interpolation Formulas in Machine Learning cites this paper.

Second-Order Path Kernel Interpolation Formulas in Machine Learning Neural Mechanics: Symmetry and Broken Conservation Laws in Deep Learning Dynamics

Reference 21

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T16:47:10.358792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 984c6536-f890-4d2c-8a13-2f5012ab0002 · inbound

Conservation Laws from Data Symmetry in Neural Networks cites this paper.

Conservation Laws from Data Symmetry in Neural Networks Neural Mechanics: Symmetry and Broken Conservation Laws in Deep Learning Dynamics

Reference 22

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T04:27:36.921807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.