Paper Citation Record · LEDGER

Clifford Group Equivariant Neural Networks

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2305.11141.

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

pith.paper-citation-record.v1
2305.11141 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:48:24.605932Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T09:09:53.219956Z

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 0905f5be-2bf5-4fec-a28f-9842062637ac · inbound

Probing Equivariance and Symmetry Breaking in Convolutional Networks cites this paper.

Probing Equivariance and Symmetry Breaking in Convolutional Networks Clifford Group Equivariant Neural Networks

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-10T22:48:24.605932Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b1ace589-9392-47e2-b9b1-a995cd4728b5 · inbound

Composing Linear Layers from Irreducibles cites this paper.

Composing Linear Layers from Irreducibles Clifford Group Equivariant Neural Networks

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:52.715395Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd87c79b-b4d1-474c-ad76-a08b4b11f41f · inbound

The Program Hypergraph: Multi-Way Relational Structure for Geometric Algebra, Spatial Compute, and Physics-Aware Compilation cites this paper.

The Program Hypergraph: Multi-Way Relational Structure for Geometric Algebra, Spatial Compute, and Physics-Aware Compilation Clifford Group Equivariant Neural Networks

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-15T08:45:19.209764Z

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 8de0be42-760f-4470-b7d5-6e6d08d1ac75 · inbound

The Program Hypergraph: Multi-Way Relational Structure for Geometric Algebra, Spatial Compute, and Physics-Aware Compilation cites this paper.

The Program Hypergraph: Multi-Way Relational Structure for Geometric Algebra, Spatial Compute, and Physics-Aware Compilation Clifford Group Equivariant Neural Networks

Reference 20

Resolution: unresolved; no resolver link, observed 2026-07-13T23:04:18.864523Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fccd4a34-8a86-4784-836b-4906c8287f5e · inbound

Adaptive Domain Models: Bayesian Evolution, Warm Rotation, and Principled Training for Geometric and Neuromorphic AI cites this paper.

Adaptive Domain Models: Bayesian Evolution, Warm Rotation, and Principled Training for Geometric and Neuromorphic AI Clifford Group Equivariant Neural Networks

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-15T09:09:53.222021Z

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 eac12f86-91f1-484d-aea5-bc9e5d70353b · inbound

Adaptive Domain Models: Bayesian Evolution, Warm Rotation, and Principled Training for Geometric and Neuromorphic AI cites this paper.

Adaptive Domain Models: Bayesian Evolution, Warm Rotation, and Principled Training for Geometric and Neuromorphic AI Clifford Group Equivariant Neural Networks

Reference 20

Resolution: unresolved; no resolver link, observed 2026-07-13T23:03:58.008815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e1e3d597-7b15-4196-bf2f-d719f9c3e9e5 · inbound

Virtues and Vices of Equivariant Transformers cites this paper.

Virtues and Vices of Equivariant Transformers Clifford Group Equivariant Neural Networks

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:49.164300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.