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Paper Citation Record · LEDGER

Geometrically Equivariant Graph Neural Networks: A Survey

As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2202.07230.

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

pith.paper-citation-record.v1
2202.07230 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T13:23:58.475909Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, 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

33
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 335c404e-e37d-430b-8f5b-0b5a4539ac66 · inbound

Adaptive Canonicalization with Application to Invariant Anisotropic Geometric Networks cites this paper.

Adaptive Canonicalization with Application to Invariant Anisotropic Geometric Networks Geometrically Equivariant Graph Neural Networks: A Survey

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-18T12:46:23.325630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-18T12:45:28.458804Z digest=sha256:ce4ac2ef23cf78c07714c4edfcd8ff4ca0fe734567d024e12075ab8d968948e9

Observation 6796aa25-55cb-437b-8a6a-ebe072715e15 · inbound

VDW-GNNs: Vector diffusion wavelets for geometric graph neural networks cites this paper.

VDW-GNNs: Vector diffusion wavelets for geometric graph neural networks Geometrically Equivariant Graph Neural Networks: A Survey

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-04T13:23:58.475909Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T13:23:58.475909Z digest=sha256:2b436187ab303640a684a1b60bc5f745aecd5505b6159482e5074b5fe2f26804

Observation 1af3adea-a798-42ac-8ecd-e2c75bd1169e · inbound

Generalized Spherical Neural Operators: Green's Function Formulation cites this paper.

Generalized Spherical Neural Operators: Green's Function Formulation Geometrically Equivariant Graph Neural Networks: A Survey

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-16T23:08:40.043383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T23:05:33.582759Z digest=sha256:7c064e86464344c2114156b46928906ce7651c7a6cacf2e1329b3438c287b211

Observation 39ff617c-26a4-4897-a5e2-2d2738a861bb · inbound

Improving Molecular Force Fields with Minimal Temporal Information cites this paper.

Improving Molecular Force Fields with Minimal Temporal Information Geometrically Equivariant Graph Neural Networks: A Survey

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-11T09:26:01.192085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-10T16:02:15.201210Z digest=sha256:e0b00bf93385698c678bc6a8cbae9783f83944a223f190a21e0c51ff813671b1

Observation 79dda163-face-4c98-8772-35cf14497f8f · inbound

Geometry-Aware Simplicial Message Passing cites this paper.

Geometry-Aware Simplicial Message Passing Geometrically Equivariant Graph Neural Networks: A Survey

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-11T18:46:09.307922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-08T14:03:46.606352Z digest=sha256:cc449de0669843cdab89f2bad40339b8709da83182ed75b6477520a8a64ae065

Observation 2cbdc426-a861-4deb-8ca8-e9a4030f9a71 · inbound

Graph Mamba Operator: A Latent Simulator for Interacting Particle Systems cites this paper.

Graph Mamba Operator: A Latent Simulator for Interacting Particle Systems Geometrically Equivariant Graph Neural Networks: A Survey

Reference 34

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T00:37:29.960069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=arxiv_source observed=2026-06-27T17:07:27.417845Z digest=sha256:802ceaf26a45e7662e8db8979c09363437ebea18b6b78b63d019f857ac5fb9f8

Observation ddc8933e-0f01-4164-a0f4-9f4f5ac8fdef · inbound

Factorized Neural Operators Decompose Dynamic and Persistent Responses cites this paper.

Factorized Neural Operators Decompose Dynamic and Persistent Responses Geometrically Equivariant Graph Neural Networks: A Survey

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-02T11:12:15.198184Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T11:12:15.198184Z digest=sha256:76870122aa8d8ceae82b4cb80a2dd93f77aa8d90fdd9627b7f1e3441ca5c4170

Observation 549b192f-676a-4e90-9d56-1b8515a88473 · inbound

Enhancing LLMs for Graph Tasks via Graph-aware LoRA Generation cites this paper.

Enhancing LLMs for Graph Tasks via Graph-aware LoRA Generation Geometrically Equivariant Graph Neural Networks: A Survey

Reference 163

Resolution
verified exact
arxiv_id, observed 2026-06-26T11:09:23.760982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=arxiv_source observed=2026-06-26T10:59:25.867813Z digest=sha256:296d853ab14c656b3d7ef8f9c89e763e46fcfc44a47a96dd6795907528d15331