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Paper Citation Record · LEDGER

Generative Diffusion Models on Graphs: Methods and Applications

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2302.02591.

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

pith.paper-citation-record.v1
2302.02591 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 2026-08-15T06:32:42.880941+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T15:03:43.548346Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T11:36:55.584808Z

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 46e64950-5e94-4a40-a5f6-5bc737b6653e · inbound

AI Tailoring: Evaluating Influence of Image Features on Fashion Product Popularity cites this paper.

AI Tailoring: Evaluating Influence of Image Features on Fashion Product Popularity Generative Diffusion Models on Graphs: Methods and Applications

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-12T15:03:43.548346Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:03:43.548346Z digest=sha256:8e59742779433ee5f1ed5a38e4f1359644c00ddba6ef512918422fd8496307da

Observation c2392437-dde8-4c9b-919e-55f6098116cf · inbound

Dynamic Entity-Masked Graph Diffusion Model for histopathological image Representation Learning cites this paper.

Dynamic Entity-Masked Graph Diffusion Model for histopathological image Representation Learning Generative Diffusion Models on Graphs: Methods and Applications

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-11T16:31:43.325867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T16:31:43.325867Z digest=sha256:e3fed301591b3e3b92affd26bd0b2b2fc5070bc70ace0f7501909f245377d90b

Observation e7959968-352c-4385-a384-1dd9768a497a · inbound

DiffCkt: A Diffusion Model-Based Hybrid Neural Network Framework for Automatic Transistor-Level Generation of Analog Circuits cites this paper.

DiffCkt: A Diffusion Model-Based Hybrid Neural Network Framework for Automatic Transistor-Level Generation of Analog Circuits Generative Diffusion Models on Graphs: Methods and Applications

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-06T21:21:13.730866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:21:13.730866Z digest=sha256:e63dd7e757e476ab13f9cb87b34a1c1d44c22b926c0e760d9298718c854915dc

Observation b2c2b11e-9689-40fa-aa75-1025407cb624 · inbound

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation cites this paper.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation Generative Diffusion Models on Graphs: Methods and Applications

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T16:36:20.606335Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:36:20.606335Z digest=sha256:d697fa8456c41b771726129c74eaf16d60be9f004dca33d00e6f443c7fc30ac3

Observation 389ef9d4-71cf-428a-9ecd-c75218059392 · inbound

Built Environment Reasoning from Remote Sensing Imagery Using Large Vision--Language Models cites this paper.

Built Environment Reasoning from Remote Sensing Imagery Using Large Vision--Language Models Generative Diffusion Models on Graphs: Methods and Applications

Reference 111

Resolution
verified exact
arxiv_id, observed 2026-05-12T08:26:24.324625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-05-12T01:10:24.579325Z digest=sha256:822c58471ea1c85178427e6ce9ffdfab354cf32895a578259be915d9a0ae0a25

Observation 76a005fd-a7c8-46fa-a45f-f0e2c4851316 · inbound

Geometric Flow Matching for Molecular Conformation Generation via Manifold Decomposition cites this paper.

Geometric Flow Matching for Molecular Conformation Generation via Manifold Decomposition Generative Diffusion Models on Graphs: Methods and Applications

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-06-29T22:24:00.735613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-06-29T22:16:46.523691Z digest=sha256:ab9763495f4bc8dabb23e7897ea8965e5f98ba2c7c1b5f4b5f96336a05e5b106

Observation 8a0a4e25-8708-4c8e-aa36-20e625f36cfe · inbound

BlockGen: Flexible Blockwise Sequence Modeling with Hybrid Samplers cites this paper.

BlockGen: Flexible Blockwise Sequence Modeling with Hybrid Samplers Generative Diffusion Models on Graphs: Methods and Applications

Reference 131

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T22:16:16.992265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-06-28T15:29:08.917412Z digest=sha256:d44117abe3417d648db6d7a680db93b0037c1c5d97fea91258aa15c422276390

Observation 614d25b9-fb27-4292-b639-f765b55499e3 · inbound

Beyond Soft Masks: Hard-Perturbation Mixup Explainer for Robust GNN Explainability cites this paper.

Beyond Soft Masks: Hard-Perturbation Mixup Explainer for Robust GNN Explainability Generative Diffusion Models on Graphs: Methods and Applications

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-07-02T11:36:55.586127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-06-28T03:10:42.043883Z digest=sha256:ca4c837dd4655f14a9e998bf95d41b9e4638ac3110db6e7688c86491879bc0ff