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Paper Citation Record · LEDGER

Sparse Training of Discrete Diffusion Models for Graph Generation

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 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 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:08:17.628989Z

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 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.

source=pdf_text observed=2026-08-07T15:08:17.628989Z digest=sha256:aba0fe30524b28b83a343147210ec38025ac0246ca1fd31afb4ae9f8d7fce3a1

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.

source=pdf_text observed=2026-08-07T11:19:34.448227Z digest=sha256:d13cfd79a2a396cda6fd024c0c2705178a540af5111f5cfaac983a4395e6f670

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.

source=pdf_text observed=2026-08-05T16:00:39.653336Z digest=sha256:e27e22bcf9dcbceca2e678cbcafdfb862a5ba37ac1803efc6d590a5537668589

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.

source=arxiv_source observed=2026-08-04T10:23:01.400115Z digest=sha256:4e1f3a8493e53104c096f1b49ac29db0f04f4910443614dd16b0d0fa11151424

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-12T01:10:24.579325Z digest=sha256:2197c697ec3725735c559f1a0b69c55b110eeccd4c140b3bde977059a03ae20f

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.

source=pdf_text observed=2026-08-02T05:17:42.578339Z digest=sha256:cd619eb49cc55f50fabf4dd15f320bec0a3ee658fe2c8c23bd11449fbf63a20e