Paper Citation Record · LEDGER

On the Benefits of Invariance in Neural Networks

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2005.00178.

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

pith.paper-citation-record.v1
2005.00178 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:49:05.103781Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T15:09:55.448306Z

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 67d0d8cb-ca07-42ea-97d1-4af1f55149e0 · inbound

On the Sample Complexity of One Hidden Layer Networks with Equivariance, Locality and Weight Sharing cites this paper.

On the Sample Complexity of One Hidden Layer Networks with Equivariance, Locality and Weight Sharing On the Benefits of Invariance in Neural Networks

Reference 2011

Resolution: unresolved; no resolver link, observed 2026-08-12T15:36:20.070947Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f97aafd7-eed0-48a4-b730-f7baa6b7e876 · inbound

Diagonal Symmetrization of Neural Network Solvers for the Many-Electron Schr\"odinger Equation cites this paper.

Diagonal Symmetrization of Neural Network Solvers for the Many-Electron Schr\"odinger Equation On the Benefits of Invariance in Neural Networks

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-08T19:53:12.669347Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 971b98d7-1492-4ccc-9e0b-068f6784d572 · inbound

Data Augmentation and Regularization for Learning Group Equivariance cites this paper.

Data Augmentation and Regularization for Learning Group Equivariance On the Benefits of Invariance in Neural Networks

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-08T15:12:22.579251Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 34dbc13c-cf0f-40ea-aa1b-7d3d2867b244 · inbound

On Equivariant Model Selection through the Lens of Uncertainty cites this paper.

On Equivariant Model Selection through the Lens of Uncertainty On the Benefits of Invariance in Neural Networks

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-15T18:49:05.103781Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3b837b52-5de0-4761-924d-3258f8ffe7d7 · inbound

Symmetries in PAC-Bayesian Learning cites this paper.

Symmetries in PAC-Bayesian Learning On the Benefits of Invariance in Neural Networks

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-04T09:11:50.522993Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 08ef3879-bd25-4cde-8bd1-38f9ea7865b4 · inbound

Aligning Network Equivariance with Data Symmetry: A Theoretical Framework and Adaptive Approach for Image Restoration cites this paper.

Aligning Network Equivariance with Data Symmetry: A Theoretical Framework and Adaptive Approach for Image Restoration On the Benefits of Invariance in Neural Networks

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-14T19:52:52.185032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2e2a6042-e8f5-47f9-be60-26ac2a4ebddf · inbound

The Evaluation Game: Beyond Static LLM Benchmarking cites this paper.

The Evaluation Game: Beyond Static LLM Benchmarking On the Benefits of Invariance in Neural Networks

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-20T07:58:07.766821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 85ba38e7-d37e-4370-a4eb-f10a4633c953 · inbound

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

Conservation Laws from Data Symmetry in Neural Networks On the Benefits of Invariance in Neural Networks

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-07-03T04:27:36.911677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e62b21af-942c-4155-9d1c-3e3f3d95a01c · inbound

Equivariance and Augmentation for Bayesian Neural Networks cites this paper.

Equivariance and Augmentation for Bayesian Neural Networks On the Benefits of Invariance in Neural Networks

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-07-04T15:09:55.450249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3e26288e-5b28-4c2e-84ab-140c69b9f79c · inbound

EquiFusion: Kinematics-Agnostic Human Motion Prediction via Equivariant Latent Diffusion cites this paper.

EquiFusion: Kinematics-Agnostic Human Motion Prediction via Equivariant Latent Diffusion On the Benefits of Invariance in Neural Networks

Reference 73

Resolution: unresolved; no resolver link, observed 2026-07-14T07:52:36.252923Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a135caa6-032e-4e9b-9cd9-606d602acc77 · inbound

PAC--Bayes Bounds on Quotient Parameter Spaces: Geometry-induced Implicit-Bias Priors cites this paper.

PAC--Bayes Bounds on Quotient Parameter Spaces: Geometry-induced Implicit-Bias Priors On the Benefits of Invariance in Neural Networks

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-01T15:35:25.250224Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.