Pith. sign in

Paper Citation Record · LEDGER

Geometrically Equivariant Graph Neural Networks: A Survey

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 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 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:14:43.359436Z

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 030c373f-92e3-414c-b8ca-825ee1512d85 · inbound

DualEquiNet: A Dual-Space Hierarchical Equivariant Network for Large Biomolecules cites this paper.

DualEquiNet: A Dual-Space Hierarchical Equivariant Network for Large Biomolecules Geometrically Equivariant Graph Neural Networks: A Survey

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T05:14:43.359436Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:14:43.359436Z digest=sha256:fee645cc811d8f947c019af4bc35556de3be698ef74b1d92c13a70c213d1faa2

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-18T12:45:28.458804Z digest=sha256:f10900d1907eeb046871d5265c2a59eaa7d9beccd5f9c7bf8dd0ae27cb152202

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=sha256:7b6ed7b81022d4a6c4254ddca96b3c39ca139d99ab72972f4a2e00136fc4d76d

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-16T23:05:33.582759Z digest=sha256:cc10ea2c87876bb5676f46ccdb79015a56bf571d63e4d297b26f5d3c23fc8f85

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T16:02:15.201210Z digest=sha256:83861bfbb0169d5fa10d922b44825865f3ce5efe39f0adfaed32ec1e0993961b

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-08T14:03:46.606352Z digest=sha256:cf3817241291e11277612ef4ef7fa00d10cacd9801eeae541942b32b97a37d06

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-27T17:07:27.417845Z digest=sha256:9d80982c5cbbbd66366ef5c2347ad73b0d29644f2cf10fcfa4e0e12cba026f31

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:df5ad44376f1fbc82722527f0b095a7ceb86ee2c67e249f4ec8b297326ed1ae5

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-26T10:59:25.867813Z digest=sha256:eedf1ce737d00193b31fac1e44cdd7608ea740d77f25e0cba79008ce7b6eb81e