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Paper Citation Record · LEDGER

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion

As of 15 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 0 inbound Pith citation observations for arXiv:2508.14352.

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

pith.paper-citation-record.v1
2508.14352 v1

Coverage vector

measured 60 of 60 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T18:43:47.431645Z

measured 60 of 60 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

60 of 60 outbound references displayed

  • verified exact1
  • verified fuzzy35
  • unresolved24
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7fc911df-7fff-499e-a9d7-479543cac96d · outbound

This paper cites Community detection and stochastic block models: recent developments.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion Community detection and stochastic block models: recent developments

Reference 1

Resolution
verified fuzzy
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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=2026-08-05T18:43:41.824991Z digest=sha256:09194090837642ea70524b0465fad52a89898d21fab0c587f5f4750b1dfd836a

Observation ce6cc871-50ea-4e4b-8577-87a8b45bbe24 · outbound

This paper cites and Mostajabdaveh, M.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion and Mostajabdaveh, M

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-05T18:43:55.057910Z

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=2026-08-05T18:43:41.896767Z digest=sha256:711e0da147c05fc067a0b79272bc786fd29adcf560e3e675b713e90bbba51179

Observation 8d7d40ec-a2bd-4b4b-a621-329f12755ec6 · outbound

This paper cites D., Ho, J., Tarlow, D., and Van Den Berg, R.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion D., Ho, J., Tarlow, D., and Van Den Berg, R

Reference 3

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raw_fallback, observed 2026-08-05T18:43:54.909419Z

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=2026-08-05T18:43:42.058307Z digest=sha256:ef669bff8b94f53bd58cf24fc80cc20f9708ae7c8b604904581e56dfc63e310a

Observation f4446d9b-8678-4784-8b10-b6e098b1ac96 · outbound

This paper cites and Albert, R.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion and Albert, R

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-05T18:43:54.682638Z

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=2026-08-05T18:43:42.174738Z digest=sha256:75ac70f4fe1081d1abf5c29417e1d8dad8f0283d424c8be2cdcef8106534205b

Observation de06eada-8b60-401e-910d-e9e272202030 · outbound

This paper cites Generative Code Modeling with Graphs.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion Generative Code Modeling with Graphs

Reference 5

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no resolver link, observed 2026-08-05T18:43:42.291589Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T18:43:42.291589Z digest=sha256:2fb37c77a2f73ec8dafbdb18adbf8e71c1a51422533204c6848c680ef1db8efb

Observation 0a2f1641-0347-45f8-ad61-af1924a68ba4 · outbound

This paper cites Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning

Reference 6

Resolution
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no resolver link, observed 2026-08-05T18:43:42.404439Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T18:43:42.404439Z digest=sha256:2d0dce065ce0cdfaba1f3ca75e8452e6b93cbf41e558ab230b0220a7ee7e8523

Observation 8a907aa3-52fc-4aae-bac6-04677b4310e2 · outbound

This paper cites Efficient and Degree-Guided Graph Generation via Discrete Diffusion Modeling.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion Efficient and Degree-Guided Graph Generation via Discrete Diffusion Modeling

Reference 7

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no resolver link, observed 2026-08-05T18:43:42.508962Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T18:43:42.508962Z digest=sha256:9e8694e81aa209fdf261e2f994856d2a11cfdca823cc55983a310424790a2b5e

Observation 1d3e8760-fc3f-42c8-bdd6-ff30f4230f86 · outbound

This paper cites K., and Lu, X.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion K., and Lu, X

Reference 8

Resolution
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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=2026-08-05T18:43:42.628198Z digest=sha256:bb423afcf05e7beb5f3f5c783e980f8945c2a62a4d03e30b92bfd1dbbef51995

Observation 29f8e18f-a0a0-4ced-a3bf-abd31f3012a8 · outbound

This paper cites Cluster-gcn: An efficient algorithm for training deep and large graph convolutional networks.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion Cluster-gcn: An efficient algorithm for training deep and large graph convolutional networks

Reference 9

Resolution
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raw_fallback, observed 2026-08-05T18:43:54.321716Z

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=2026-08-05T18:43:42.750634Z digest=sha256:cbc318b7284aa79aad13a41a7902b53e6e404d9cdc919836932c399fd3821efd

Observation 9f3b41a2-8503-49ad-8364-8c7f0b7a0199 · outbound

This paper cites an unresolved cited work.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion Unresolved cited work

Reference 10

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no resolver link, observed 2026-08-05T18:43:42.833963Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T18:43:42.833963Z digest=sha256:3817130f48318d3ca5229003ac6e70ad577dc4ffa4f32bf5c06d72b630de9346

Observation a4cb7e54-85e1-4e89-b087-9910e689de2d · outbound

This paper cites Contextual stochastic block models.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion Contextual stochastic block models

Reference 11

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verified fuzzy
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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=2026-08-05T18:43:42.936496Z digest=sha256:6fff2cd43c7ceb7ac685232f46e7a424d99d7147d1c884cbe8f0fbfa96a5db9b

Observation a65e4da6-6778-459d-8b2e-5ad7ca426764 · outbound

This paper cites and Nichol, A.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion and Nichol, A

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T18:43:43.095213Z digest=sha256:783e23619181d1f1192488ae64afdeccbdf26246bd1d0ffb2262fcd54588fcea

Observation a102337e-7727-4ab0-a2f9-71b5b7075a63 · outbound

This paper cites an unresolved cited work.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion Unresolved cited work

Reference 13

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raw_fallback, observed 2026-08-05T18:43:53.853079Z

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=2026-08-05T18:43:43.201513Z digest=sha256:264694a01f9e33b303bda698bb14908ba761c8519d900e36607e620b8643b2dd

Observation a66a4a29-0541-4e34-a164-1131dae1a5a0 · outbound

This paper cites On the evolution of random graphs.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion On the evolution of random graphs

Reference 14

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verified fuzzy
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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=2026-08-05T18:43:43.314921Z digest=sha256:2ab7be05146979f02345aecf39c5527d79145baa655abd13ff7b6ed8a3c90e28

Observation b69aee61-cbd7-4b10-984f-787eb2dbcb1c · outbound

This paper cites Algebraic connectivity of graphs.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion Algebraic connectivity of graphs

Reference 15

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verified fuzzy
raw_fallback, observed 2026-08-05T18:43:53.484311Z

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=2026-08-05T18:43:43.392680Z digest=sha256:38de538c0c07d79253a9f204a92203d109f4295cf7707207e2bf5ab62d9cac58

Observation 4f33f947-f095-4153-982f-117e0a28b712 · outbound

This paper cites M., Rasch, M.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion M., Rasch, M

Reference 16

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verified fuzzy
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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=2026-08-05T18:43:43.447562Z digest=sha256:2604eec5055c4517e125851d106bdd6fc8ea4872b659422f764ac2563769280f

Observation da91e25a-1147-460f-a3b1-202025ce129e · outbound

This paper cites Graphite: Iterative generative modeling of graphs.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion Graphite: Iterative generative modeling of graphs

Reference 17

Resolution
verified fuzzy
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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=2026-08-05T18:43:43.567145Z digest=sha256:e8ca50c628e0007b131d6d44aa75cb7a272c3befb3787f925895ca5091f60cf4

Observation 589b772a-55ff-44d1-a169-683d7ca24664 · outbound

This paper cites L., Ying, R., and Leskovec, J.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion L., Ying, R., and Leskovec, J

Reference 18

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unresolved
no resolver link, observed 2026-08-05T18:43:43.691915Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T18:43:43.691915Z digest=sha256:31de0a18b8fd7d780ccd9de7cf6343af792ffb7e71e842f7ba807bc4c9816ec1

Observation 99700b15-c1d0-475a-a537-e4245d3d57cb · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilibrium.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion Gans trained by a two time-scale update rule converge to a local nash equilibrium

Reference 19

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source=arxiv_source observed=2026-08-05T18:43:43.775710Z digest=sha256:10283b8827b509aef47439c01a2cfe02cbb09308f0dc12d5e96e8b829194715b

Observation b77997d9-c5ae-4a66-b135-da3935eaab40 · outbound

This paper cites Denoising diffusion probabilistic models.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion Denoising diffusion probabilistic models

Reference 20

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no resolver link, observed 2026-08-05T18:43:43.928063Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T18:43:43.928063Z digest=sha256:37cda8e1752e8009178747d2d5e9193245466345ab30fe65c39c10c182503f31

Observation 61548850-0368-409d-ab8a-41a83b0e733e · outbound

This paper cites W., Laskey, K.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion W., Laskey, K

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:43:52.912392Z

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=2026-08-05T18:43:44.024639Z digest=sha256:17840711398266ce3e6890aff8ad79c5db5e7f7355c3215acf3377ffe8e50b6f

Observation 9a73a455-b9ec-479e-b3c9-44fc41e62056 · outbound

This paper cites Argmax flows and multinomial diffusion: Learning categorical distributions.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion Argmax flows and multinomial diffusion: Learning categorical distributions

Reference 22

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verified fuzzy
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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=2026-08-05T18:43:44.102395Z digest=sha256:7af1cd0f3a7a72dd12184d7411a55ce4b0b8732595e2d6d4cb223067fcd3edeb

Observation 3abc0a6f-d97e-4720-a462-38995d49bdec · outbound

This paper cites Open Graph Benchmark: Datasets for Machine Learning on Graphs.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 23

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no resolver link, observed 2026-08-05T18:43:44.238519Z

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source=arxiv_source observed=2026-08-05T18:43:44.238519Z digest=sha256:2ff769d3c32ec59cd51f0a9c0c73e809c8f3e81f203975ecffbecd8ab5256e92

Observation 7ed7b108-fd42-4f53-b9b0-019d61390a9b · outbound

This paper cites an unresolved cited work.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion Unresolved cited work

Reference 24

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

source=arxiv_source observed=2026-08-05T18:43:44.367271Z digest=sha256:2fcc84b9d78731a5d6327778cdd3182cae941ded7d0776a9402cc755a78038e0

Observation 99470b79-4b42-41b5-9d62-5017fa4ad861 · outbound

This paper cites Graph Generation with Diffusion Mixture.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion Graph Generation with Diffusion Mixture

Reference 25

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no resolver link, observed 2026-08-05T18:43:44.490134Z

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source=arxiv_source observed=2026-08-05T18:43:44.490134Z digest=sha256:654057d20cf1837c9d59c854b862c034ce4fd7ec73fd0a052866cca673e3a1d8

Observation 1372991e-f883-4b9e-a221-deef98c517bf · outbound

This paper cites An algorithm for drawing general undirected graphs.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion An algorithm for drawing general undirected graphs

Reference 26

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raw_fallback, observed 2026-08-05T18:43:52.381273Z

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

source=arxiv_source observed=2026-08-05T18:43:44.566380Z digest=sha256:8b2d44bc00a9a9e2b2eafac0a1c429611cff4de110f0749ed98ce4f3e5b7d9b7

Observation 717924c2-1be8-4f7e-8911-d24fe4d3c7ef · outbound

This paper cites and Newman, M.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion and Newman, M

Reference 27

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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=2026-08-05T18:43:44.678391Z digest=sha256:0627e9a55eadd10abccf0853405b8dd60bd4615305c6be385a6d0c6cba5578f4

Observation 18a07705-0e6a-4232-9d2e-aac774fb853d · outbound

This paper cites and Kumar, V.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion and Kumar, V

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:43:51.897492Z

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=2026-08-05T18:43:44.763489Z digest=sha256:fb067d418a80cb0045653f974b73c6506a34a42b22e8bd8e0bd8cc063d451e75

Observation 5fc34092-e415-4eca-9931-3fbe962a463f · outbound

This paper cites H., Vygen, J., Korte, B., and Vygen, J.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion H., Vygen, J., Korte, B., and Vygen, J

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:43:51.652911Z

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=2026-08-05T18:43:44.898753Z digest=sha256:bd545120619538db9b334f941f8d0c8e1f808d2a1fc181acab264dcc6f67500d

Observation daf9be7d-bd96-4194-86f9-31fa7ebc2dd1 · outbound

This paper cites Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets

Reference 30

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verified exact
local_arxiv, observed 2026-08-05T18:43:47.767898Z

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=2026-08-05T18:43:45.026960Z digest=sha256:500f7a624e372c7e1ea34f9495d23eef2e4102788979b582c53dee75004a91c3

Observation c4b7c48a-91db-46b9-860b-cac24aac85ce · outbound

This paper cites Multi-objective de novo drug design with conditional graph generative model.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion Multi-objective de novo drug design with conditional graph generative model

Reference 31

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verified fuzzy
raw_fallback, observed 2026-08-05T18:43:51.420287Z

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=2026-08-05T18:43:45.140280Z digest=sha256:6e66ec7dbb4fe5088bc37aff77dd3d07e8b32d579df83c972a7e568857c5cafc

Observation 4785d16b-482d-40b0-9bbc-dc7ea992149a · outbound

This paper cites Spectre: Spectral conditioning helps to overcome the expressivity limits of one-shot graph generators.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion Spectre: Spectral conditioning helps to overcome the expressivity limits of one-shot graph generators

Reference 32

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verified fuzzy
raw_fallback, observed 2026-08-05T18:43:51.222529Z

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=2026-08-05T18:43:45.222950Z digest=sha256:fc9ff227cc3f5ebd8b52d4a1519cebd68cd2365eebf0ca6b7ddb882c9facd62b

Observation 2950fe36-3fc1-4d8e-89bf-b2d541e1150c · outbound

This paper cites an unresolved cited work.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion Unresolved cited work

Reference 33

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

source=arxiv_source observed=2026-08-05T18:43:45.291323Z digest=sha256:196713b837ce172e3225f9569d574dfdef5d503b05af44fcb8c95a6477c9fc34

Observation 365a001a-5edb-4b93-8327-8b2a635b2ba3 · outbound

This paper cites an unresolved cited work.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion Unresolved cited work

Reference 34

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unresolved
raw_fallback, observed 2026-08-05T18:43:50.745222Z

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=2026-08-05T18:43:45.415614Z digest=sha256:3c13fa4283db388a0a477fceb0ad6bd77f4cf96cda8b58208adee91a3c17daa4

Observation 7a338fce-4cf7-4beb-a037-c9e454432f17 · outbound

This paper cites E., Watts, D.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion E., Watts, D

Reference 35

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verified fuzzy
raw_fallback, observed 2026-08-05T18:43:50.524463Z

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=2026-08-05T18:43:45.568462Z digest=sha256:6f2bd932fcb1e9926ac14159a54a70b48a2caad6f72eb433a5514a2f6e86e1d4

Observation 28445504-8ab3-4e5f-8d7e-ac12ab18b8cc · outbound

This paper cites GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models

Reference 36

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unresolved
no resolver link, observed 2026-08-05T18:43:45.687762Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T18:43:45.687762Z digest=sha256:292dd1e23598b82d6933c9bc5a23088efa0cef16529e66eb3d59995152517876

Observation bcbf2c0e-ebc1-42a7-9d97-b8032240030d · outbound

This paper cites Permutation invariant graph generation via score-based generative modeling.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion Permutation invariant graph generation via score-based generative modeling

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:43:50.299093Z

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=2026-08-05T18:43:45.760808Z digest=sha256:506a0aa082cdba4558c7c011b2aaba89459f028561ffca5133cf07011b9742ed

Observation c849699e-e6e0-4fd7-80dd-e92be3313527 · outbound

This paper cites Deepwalk: Online learning of social representations.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion Deepwalk: Online learning of social representations

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:43:50.063970Z

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=2026-08-05T18:43:45.844016Z digest=sha256:5f2d38604c0ea65475cc31158e651910e7b6c1d972fa0994c59da416ca2ffba4

Observation aac2fd38-02b4-462e-a07e-cf914e2105cd · outbound

This paper cites Fr \'e chet chemnet distance: a metric for generative models for molecules in drug discovery.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion Fr \'e chet chemnet distance: a metric for generative models for molecules in drug discovery

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:43:49.852431Z

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=2026-08-05T18:43:45.949569Z digest=sha256:b74546508bf1e6931c2337f4f6ea2d169bd98a253db134923f39a2936e71fc8f

Observation 691e028d-32c7-425b-bb6e-06b019fe92aa · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion High-resolution image synthesis with latent diffusion models

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-05T18:43:46.089605Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T18:43:46.089605Z digest=sha256:90c37db4ed4acee9269c179d46b3e966cd3acfa0677014ce113357a4306d5516

Observation a27da479-1817-4c42-b951-2554f1982852 · outbound

This paper cites and Komodakis, N.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion and Komodakis, N

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:43:49.674085Z

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=2026-08-05T18:43:46.171003Z digest=sha256:de3e0a09be29eed6cbfc7bd6714704e069caec948518d7337b27a5472607978d

Observation 99661844-0161-4856-9fcf-2b3834b66c84 · outbound

This paper cites Deep unsupervised learning using nonequilibrium thermodynamics.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion Deep unsupervised learning using nonequilibrium thermodynamics

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:43:49.540030Z

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=2026-08-05T18:43:46.253052Z digest=sha256:13d48e1b0a245f06d2b463fce9c8d98be9b51f80d9d282bfd306b665c5fe3034

Observation bddf4839-dff6-415a-881d-492ea7138bfd · outbound

This paper cites Denoising Diffusion Implicit Models.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion Denoising Diffusion Implicit Models

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-05T18:43:46.310247Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T18:43:46.310247Z digest=sha256:ca8951ee09d75370898ba33e6498b340edda16d3701576b14082f7f87784a5a0

Observation 910390c2-c6c5-4cfe-acb7-4586f6ac6340 · outbound

This paper cites and Ermon, S.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion and Ermon, S

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-05T18:43:46.372574Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T18:43:46.372574Z digest=sha256:3b2f9ca02a227636a35aecf8a3f69a54aa52c0fdb2be23c49aeb904d3519a597

Observation 33597382-bafc-49d4-91f9-369b3a0ed2ba · outbound

This paper cites and Ermon, S.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion and Ermon, S

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:43:49.332701Z

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=2026-08-05T18:43:46.413688Z digest=sha256:a4610c5e76b2a35ec696e8486411ac40a50ecbe95a4d5d19dfb93fc0b0b9a5ef

Observation c2005827-6097-482f-9669-7c49dc40040a · outbound

This paper cites Score-Based Generative Modeling through Stochastic Differential Equations.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion Score-Based Generative Modeling through Stochastic Differential Equations

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-05T18:43:46.468600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T18:43:46.468600Z digest=sha256:db30b3bc11441d9cdbfb0ccf1baa05d57e76dfd64a7af56dfcb9a93f5d8e33f9

Observation 883ae1ee-e3cc-4dd2-a4a6-4f6644bf2906 · outbound

This paper cites and Marbach, P.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion and Marbach, P

Reference 47

Resolution
verified fuzzy
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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=2026-08-05T18:43:46.550770Z digest=sha256:666d09e29996a0a598b0b5c425bd3630c70aabec5963641e217c61c206faeed2

Observation 0e44d8e8-a94d-4caf-85c1-3a1567c980a1 · outbound

This paper cites and Marbach, P.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion and Marbach, P

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:43:49.022506Z

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=2026-08-05T18:43:46.615224Z digest=sha256:94f00e886fbfd8f9a848ec92f68c7ab40f32f05ec3c6faecb7ba40ae11a856c5

Observation e41b1110-7d3f-4694-88c9-a76f22234ff1 · outbound

This paper cites On Evaluation Metrics for Graph Generative Models.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion On Evaluation Metrics for Graph Generative Models

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-05T18:43:46.695271Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T18:43:46.695271Z digest=sha256:ad20236cd47b4f991f1bb26e099976fe09ec2596c8933f0720d2c7fd80a941bf

Observation e29653dd-e1a5-4298-85a5-e9a03f58b3cb · outbound

This paper cites DiGress: Discrete Denoising diffusion for graph generation.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion DiGress: Discrete Denoising diffusion for graph generation

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-05T18:43:46.757680Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T18:43:46.757680Z digest=sha256:707a3cf1439dad4c5423d01d0ce8c2fd6604358fc7611f0e81530b02d30d4ac6

Observation df4caba9-0629-48af-a2ef-10bbd4828306 · outbound

This paper cites Graphgan: Graph representation learning with generative adversarial nets.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion Graphgan: Graph representation learning with generative adversarial nets

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:43:48.887240Z

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=2026-08-05T18:43:46.814757Z digest=sha256:86a092e3619113817fea7a12ce1f4b9f00f20ebf2ed4f3393e019b5cfcb764e9

Observation b389fc51-6cac-45b7-99d4-59377d766ecb · outbound

This paper cites Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-05T18:43:46.881653Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T18:43:46.881653Z digest=sha256:72a4d19ba1499d4bbd4468e6f3bd79a7d80ed82c1957b635f480849f727b636e

Observation 3c060774-851c-40fe-9957-e92f3aec9f64 · outbound

This paper cites A compact review of molecular property prediction with graph neural networks.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion A compact review of molecular property prediction with graph neural networks

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:43:48.739508Z

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=2026-08-05T18:43:46.970028Z digest=sha256:5f6ebbc181c5d4f3dcdb59866f96581fe553b1fee7b2a96f25aee4714088d6ac

Observation d5224118-99e9-4a6c-869a-52febf72d32c · outbound

This paper cites N., Gomes, J., Geniesse, C., Pappu, A.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion N., Gomes, J., Geniesse, C., Pappu, A

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:43:48.593389Z

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=2026-08-05T18:43:47.051373Z digest=sha256:04670ddba2c8b3cb3b55f2bd7f51af337cd00a9d36f8121fae16df091e3b6d99

Observation 1133588e-d4ac-4b84-b629-f53bf0fb5a45 · outbound

This paper cites Exploring randomly wired neural networks for image recognition.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion Exploring randomly wired neural networks for image recognition

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:43:48.464511Z

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=2026-08-05T18:43:47.091442Z digest=sha256:dee4370a7de9ff4611f34ab580978186a741751e130ed2f6ce0e9824195e3697

Observation 11ad67f9-177f-4578-921d-92ade37e9db5 · outbound

This paper cites Poisson flow generative models, 2022.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion Poisson flow generative models, 2022

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:43:48.331713Z

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=2026-08-05T18:43:47.159481Z digest=sha256:80cfab38011d437385f671fab11265bd3bc8dd626d791048e84f90189d8a63a6

Observation 4ac4972b-fe30-451b-ad85-b0911a8d3bdb · outbound

This paper cites Diffsound: Discrete diffusion model for text-to-sound generation.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion Diffsound: Discrete diffusion model for text-to-sound generation

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:43:48.187818Z

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=2026-08-05T18:43:47.220093Z digest=sha256:e2b08826dfb9d5065889593e8a00560a37d851ac06c2a1198221f43580391dca

Observation 6282df0d-bd51-4c14-85d9-0ce9bd80a5d2 · outbound

This paper cites Graphrnn: Generating realistic graphs with deep auto-regressive models.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion Graphrnn: Generating realistic graphs with deep auto-regressive models

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:43:48.048822Z

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=2026-08-05T18:43:47.281628Z digest=sha256:020c5dd55b63756225cbabf4d0ed52642bc4095b9e44f698777a0e9d8cb59f85

Observation d440e090-f460-4f07-ae26-dd6ba85b1e84 · outbound

This paper cites Pard: Permutation-Invariant Autoregressive Diffusion for Graph Generation.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion Pard: Permutation-Invariant Autoregressive Diffusion for Graph Generation

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-05T18:43:47.352812Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T18:43:47.352812Z digest=sha256:8ef8d8f918fc19ddd05c95a8b7704d3fe785ac31cf87dd5cdd5510d64e5c0ac3

Observation 5876be90-f38c-4b11-9770-06f47c4571aa · outbound

This paper cites write newline.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion write newline

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-05T18:43:47.431645Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T18:43:47.431645Z digest=sha256:18ef280d1ab3e4f83c04237018e64cf6a4f6128181d10b88cece6deeb21f5f26

Pith citing papers

No inbound Pith citation observations are available.