Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Neural Mechanics: Symmetry and Broken Conservation Laws in Deep Learning Dynamics
As of 18 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.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T06:06:57.442994Z
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 2026-08-18T06:34:40.430872+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 2026-08-18T06:34:40.430872+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 2026-08-18T06:34:40.430872+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 2026-08-18T06:34:40.430872+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 2026-08-18T06:34:40.430872+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 2026-08-18T06:34:40.430872+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 2026-08-18T06:34:40.430872+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 2026-08-18T06:34:40.430872+00:00.