Paper Citation Record · LEDGER

Sparse Training of Discrete Diffusion Models for Graph Generation

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2311.02142.

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

pith.paper-citation-record.v1
2311.02142 v2

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 2026-08-22T06:32:14.747728+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T15:20:40.252172Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T08:26:24.335548Z

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 d96fcdf3-3620-4594-9566-442d40ffb1a8 · inbound

TFG-Flow: Training-free Guidance in Multimodal Generative Flow cites this paper.

TFG-Flow: Training-free Guidance in Multimodal Generative Flow Sparse Training of Discrete Diffusion Models for Graph Generation

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-10T15:20:40.252172Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 182bfb17-8aa2-445e-8191-a5ba66c22823 · inbound

A collaborative constrained graph diffusion model for the generation of realistic synthetic molecules cites this paper.

A collaborative constrained graph diffusion model for the generation of realistic synthetic molecules Sparse Training of Discrete Diffusion Models for Graph Generation

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T15:08:17.628989Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c59b0eb-22eb-42d8-aa23-602d5de7dc45 · inbound

FreeScene: Mixed Graph Diffusion for 3D Scene Synthesis from Free Prompts cites this paper.

FreeScene: Mixed Graph Diffusion for 3D Scene Synthesis from Free Prompts Sparse Training of Discrete Diffusion Models for Graph Generation

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T11:19:34.448227Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a1021e2-4849-4d70-a11a-75030ddeedd2 · inbound

SynCircuit: Automated Generation of New Synthetic RTL Circuits Can Enable Big Data in Circuits cites this paper.

SynCircuit: Automated Generation of New Synthetic RTL Circuits Can Enable Big Data in Circuits Sparse Training of Discrete Diffusion Models for Graph Generation

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-05T16:00:39.653336Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3fd5c953-220c-4a74-aac1-b50b1655b9e3 · inbound

Discrete State Diffusion Models: A Sample Complexity Perspective cites this paper.

Discrete State Diffusion Models: A Sample Complexity Perspective Sparse Training of Discrete Diffusion Models for Graph Generation

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-04T10:23:01.400115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d6a3b787-1e0f-41ea-8c05-2dc033f02562 · 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 Sparse Training of Discrete Diffusion Models for Graph Generation

Reference 150

Resolution: verified exact; arxiv_id, observed 2026-05-12T08:26:24.338363Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7749659c-1f16-411d-8ec0-01ae7b4de92a · inbound

Discrete Diffusion Models: A Unified Framework from Tokenization to Generation cites this paper.

Discrete Diffusion Models: A Unified Framework from Tokenization to Generation Sparse Training of Discrete Diffusion Models for Graph Generation

Reference 144

Resolution: unresolved; no resolver link, observed 2026-08-02T05:17:42.578339Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.