Pith. sign in

Paper Citation Record · LEDGER

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models

As of 8 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2505.22935.

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

pith.paper-citation-record.v1
2505.22935 v2

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:01:53.363678Z

measured 45 of 45 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 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

45 of 45 outbound references displayed

  • verified exact3
  • verified fuzzy23
  • unresolved17
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 550daa1d-2cf0-4825-b077-1a0580ce4676 · outbound

This paper cites Diffusion models beat gans on image synthesis.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Diffusion models beat gans on image synthesis

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:02:01.733594Z

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=pdf_text observed=2026-08-07T13:01:48.579937Z digest=sha256:12c94f7ea2675a336b16d5d0c216233774a72d5790c606ccdb8048becae89a7e

Observation 41596a75-1385-4c26-ba7f-5e6dee3ebc3c · outbound

This paper cites Weiss, Mohammad Norouzi, and William Chan.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Weiss, Mohammad Norouzi, and William Chan

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:02:01.457035Z

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=pdf_text observed=2026-08-07T13:01:48.667143Z digest=sha256:45aa03c2ac2c4410311ac5848f05bff2c034ea59ae60e427e3b36d7d91821a1e

Observation 21ee3500-5d32-429d-afa4-e4ce6236bb78 · outbound

This paper cites Diffwave: A versatile diffusion model for audio synthesis.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Diffwave: A versatile diffusion model for audio synthesis

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:02:01.182583Z

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=pdf_text observed=2026-08-07T13:01:48.734647Z digest=sha256:21bbce48b3d45dcb0abe25ac027a9eabdafbfb228548fe002ec735b3c36ceb2f

Observation a0b38dfa-c1ea-4e2c-90ea-059e1470a6da · outbound

This paper cites Diffusion probabilistic models for 3d point cloud generation.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Diffusion probabilistic models for 3d point cloud generation

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:02:00.951494Z

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=pdf_text observed=2026-08-07T13:01:48.795601Z digest=sha256:5137cae137ce613e83190808bc7797370602583486e6be5397923a180b88d99b

Observation 15936408-c82c-4d14-a7d5-f54c8327b5e2 · outbound

This paper cites Geodiff: A geometric diffusion model for molecular conformation generation.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Geodiff: A geometric diffusion model for molecular conformation generation

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:02:00.729002Z

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=pdf_text observed=2026-08-07T13:01:48.923484Z digest=sha256:5c4988a2bee22d49911d7be6037c5c0534f8b07729bb656594f14820f086f57e

Observation 61009879-feeb-4f84-a8c9-ef702f8e3328 · outbound

This paper cites Difusco: Graph-based diffusion solvers for combinatorial optimization.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Difusco: Graph-based diffusion solvers for combinatorial optimization

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:02:00.533500Z

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=pdf_text observed=2026-08-07T13:01:49.001202Z digest=sha256:65f7830487a4d9191630719a2a0b40f359ceba78480ccd33c6b52bb91ccb43c8

Observation de6ea5ca-b90e-4b7c-8039-788ea73d4bf8 · outbound

This paper cites DiGress: Discrete diffusion for graph generation.Advances in Neural Information Processing Systems (NeurIPS), 2022.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models DiGress: Discrete diffusion for graph generation.Advances in Neural Information Processing Systems (NeurIPS), 2022

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:02:00.331767Z

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=pdf_text observed=2026-08-07T13:01:49.127417Z digest=sha256:b37a109ebcfa94fab54281de3b3ef10ba83ac907bcc4cff145e38f4a00482838

Observation 4678c830-fa4f-47d0-8d86-01b7eb98b27f · outbound

This paper cites Denoising diffusion probabilistic models.Advances in Neural Information Processing Systems (NeurIPS), 33:6840–6851, 2020.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Denoising diffusion probabilistic models.Advances in Neural Information Processing Systems (NeurIPS), 33:6840–6851, 2020

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T13:01:49.208658Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:01:49.208658Z digest=sha256:9fb1f09101d83594e9f1173928bbac8475e2f8a942778d27d6416d74e8e7dcf9

Observation 69e9c9df-2896-4b7c-927b-c9bc68be813a · outbound

This paper cites Score-based generative modeling through stochastic differential equations.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Score-based generative modeling through stochastic differential equations

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T13:01:49.311445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:01:49.311445Z digest=sha256:6c7aec746075c29427bca6164f2b6ff3571a9481584f256659b94caf710d5464

Observation 4b7acbaa-75c6-4361-b294-2914bb6a8a36 · outbound

This paper cites Is noise conditioning necessary for denoising generative models?, 2025.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Is noise conditioning necessary for denoising generative models?, 2025

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T13:01:49.405620Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:01:49.405620Z digest=sha256:9581f19371d980806cff0d06a2663a54024de9d32e7a74473fdee80f9b548768

Observation 0e569455-2a86-47d1-a088-d612682f5451 · outbound

This paper cites Margossian, Ruben Ohana, and Bruno Régaldo-Saint Blan- card.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Margossian, Ruben Ohana, and Bruno Régaldo-Saint Blan- card

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:02:00.122976Z

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=pdf_text observed=2026-08-07T13:01:49.496541Z digest=sha256:334dcb5943b01548119bd738884a4c4eed576b5504e078d29689918397145488

Observation 00dda2ec-34b2-4edc-9373-eba9ebb09847 · outbound

This paper cites Dif- fusion models with learned adaptive noise.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Dif- fusion models with learned adaptive noise

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:01:59.913578Z

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=pdf_text observed=2026-08-07T13:01:49.591117Z digest=sha256:8954658fb6af8dcc6f10e60c7b94d8ed99bbed896c7bfb3b222721abf33eebd1

Observation d3fe70ab-e0ba-46bb-aae8-7114bfedaa12 · outbound

This paper cites Non Gaussian Denoising Diffusion Models.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Non Gaussian Denoising Diffusion Models

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T13:01:49.663095Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:01:49.663095Z digest=sha256:96c6351e7b2a49b36be731eb0121cfa670d6ba146476115a1f57b034fb46fb65

Observation bf100ad1-127a-4e39-bb10-d26d063f5a3b · outbound

This paper cites Diffusion Models for Graphs Benefit From Discrete State Spaces.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Diffusion Models for Graphs Benefit From Discrete State Spaces

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T13:01:49.772369Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:01:49.772369Z digest=sha256:705f80d19d763eb45690d26c49e48035a4d8e7ab983676f495b631f838f2d7d5

Observation a29f25dc-26af-4b96-9e24-45215b20bade · outbound

This paper cites GraphGUIDE: interpretable and controllable conditional graph generation with discrete Bernoulli diffusion.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models GraphGUIDE: interpretable and controllable conditional graph generation with discrete Bernoulli diffusion

Reference 15

Resolution
metadata mismatch
local_arxiv, observed 2026-08-07T13:01:54.677493Z

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=pdf_text observed=2026-08-07T13:01:49.865648Z digest=sha256:17e93dc2f411bace972699d21a78186cdf896ab5b555fd34a749b73cd967a233

Observation 7d46e506-a48d-4e03-963a-e98ad23dfeb9 · outbound

This paper cites Johnson, Jonathan Ho, Daniel Tarlow, and Rianne van den Berg.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Johnson, Jonathan Ho, Daniel Tarlow, and Rianne van den Berg

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:01:59.681152Z

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=pdf_text observed=2026-08-07T13:01:49.933261Z digest=sha256:ced35a54c2f7dd097895c4a878c8ba108f518894ab2606e097d1247c1086be42

Observation 4b87ea2f-7002-4dde-bbc4-5c0073882af2 · outbound

This paper cites Discrete-state Continuous-time Diffusion for Graph Generation.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Discrete-state Continuous-time Diffusion for Graph Generation

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T13:01:50.016296Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:01:50.016296Z digest=sha256:af26a2af3343bcd805439458bcc6916f78494251ae3218cc6fad56aa408d8097

Observation 41dc0826-62a2-4fab-af6e-24b71836f130 · outbound

This paper cites Score-based generative modeling of graphs via the system of stochastic differential equations.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Score-based generative modeling of graphs via the system of stochastic differential equations

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:01:59.458578Z

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=pdf_text observed=2026-08-07T13:01:50.129328Z digest=sha256:21cefa7341d11f0add2b4fbdf6d7f7ac792e162335f046000e30e715faff7908

Observation a8106df5-3721-41e0-b479-a38e363ddcb4 · outbound

This paper cites Deep unsuper- vised learning using nonequilibrium thermodynamics.International Conference on Machine Learning (ICML), pages 2256–2265, 2015.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Deep unsuper- vised learning using nonequilibrium thermodynamics.International Conference on Machine Learning (ICML), pages 2256–2265, 2015

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:01:59.227149Z

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=pdf_text observed=2026-08-07T13:01:50.273847Z digest=sha256:999ba3a424d274384ab2193cb64d84ef574ed2733b6101bce0178116c32c7d21

Observation aa9996f4-28ac-4ec9-91bf-bb6443172b8c · outbound

This paper cites Equivariant Diffusion for Molecule Generation in 3D.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Equivariant Diffusion for Molecule Generation in 3D

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-07T13:01:50.449886Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:01:50.449886Z digest=sha256:99cd10d98981b6f1d84ed5b41772096f257aa666b5cbfec454ae8ad92fccf0d6

Observation b9bdb079-1628-4264-8d09-df58b5868b5e · outbound

This paper cites Noise2self: Blind denoising by self-supervision.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Noise2self: Blind denoising by self-supervision

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:01:58.918535Z

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=pdf_text observed=2026-08-07T13:01:50.593410Z digest=sha256:58b32401aab170f942b7d251cc7e30d93ac9e0600dd77e920220120a792238d5

Observation ff738497-8cc0-48ff-b98a-06e51e875776 · outbound

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

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Permutation invariant graph generation via score-based generative modeling

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:01:58.621016Z

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=pdf_text observed=2026-08-07T13:01:50.710690Z digest=sha256:f75d459a8315494270cced9668193967db8702512e20f9c974a872c4bff35a8a

Observation 9eda7613-88cb-41da-85fa-d3ccfa7e33a7 · outbound

This paper cites Hyperbolic graph diffusion model.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Hyperbolic graph diffusion model

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:01:58.382652Z

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=pdf_text observed=2026-08-07T13:01:50.859754Z digest=sha256:793d20d4f7a38adf4450de7b49d4b09ebf8413c33dea87d1632020f2635c8e3f

Observation e8c3004a-cb9b-4f6e-bcff-0d4692d120e6 · outbound

This paper cites Advancing Graph Generation through Beta Diffusion.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Advancing Graph Generation through Beta Diffusion

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-07T13:01:50.966144Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:01:50.966144Z digest=sha256:4df1a7c02c0397cdeef521385fba260f025e4d42079b4f9427dd11d23736e043

Observation 72b7c63b-67f6-40d8-9c5b-3bc9c576a7b9 · outbound

This paper cites Fisher information and stochastic complexity.IEEE transactions on information theory, 42(1):40–47, 1996.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Fisher information and stochastic complexity.IEEE transactions on information theory, 42(1):40–47, 1996

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:01:58.077018Z

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=pdf_text observed=2026-08-07T13:01:51.052086Z digest=sha256:ffe3818ef166a4e1b230efe2e78888334b8ac3cb4a1fbd27d52fecd9335ed891

Observation 4af7c889-f951-4c28-9bdc-a81e810323d7 · outbound

This paper cites an unresolved cited work.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Unresolved cited work

Reference 26

Resolution
unresolved
raw_fallback, observed 2026-08-07T13:01:57.807871Z

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=pdf_text observed=2026-08-07T13:01:51.163754Z digest=sha256:e533447b01928935ecd6720711695d7696e439865862aed5e788a0fbbaa68ae4

Observation c43db5ef-e297-48bb-b711-f3567735349c · outbound

This paper cites an unresolved cited work.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Unresolved cited work

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-07T13:01:51.281331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:01:51.281331Z digest=sha256:c40dd610290197303d4c4f203f8e3eeae69c07e975a878fb62da5dde7476d886

Observation 5830799c-fe72-40cd-a0c8-f0d295f6405d · outbound

This paper cites Higher-order interactions shape col- lective dynamics differently in hypergraphs and simplicial complexes.Nature Communications, 14:1605, 2023.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Higher-order interactions shape col- lective dynamics differently in hypergraphs and simplicial complexes.Nature Communications, 14:1605, 2023

Reference 28

Resolution
verified exact
doi, observed 2026-08-07T13:01:53.653840Z

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=pdf_text observed=2026-08-07T13:01:51.394872Z digest=sha256:8bbee14987c40d8a1fdc92d20c37d39b2dedba1521bf17a29ec2db7e50afc4ba

Observation 5322f021-53e5-4a39-80c0-442dd947648c · outbound

This paper cites Dynamic networks and behavior: Separating selection from influence.Sociological methodology, 40(1):329–393, 2010.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Dynamic networks and behavior: Separating selection from influence.Sociological methodology, 40(1):329–393, 2010

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:01:57.541743Z

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=pdf_text observed=2026-08-07T13:01:51.498690Z digest=sha256:10b0369d2bd4d14225341feee543c7f7913f790a9b1917a78f4ee80a29b52d7e

Observation b194b303-c3e8-46c0-8cb0-818bf6f76d52 · outbound

This paper cites Complex contagion process in spreading of online innovation.Journal of the Royal Society Interface, 11(101):20140694,.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Complex contagion process in spreading of online innovation.Journal of the Royal Society Interface, 11(101):20140694,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:01:57.270114Z

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=pdf_text observed=2026-08-07T13:01:51.609627Z digest=sha256:5fd72d6544b6f7b27641c024cdf59a65263cc6ad104009431fc3ccf4e7c3edb3

Observation 39fa7d3f-afe2-4869-bf46-28707fc15375 · outbound

This paper cites Gnnguard: Defending graph neural networks against adversarial attacks.arXiv preprint, 2020.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Gnnguard: Defending graph neural networks against adversarial attacks.arXiv preprint, 2020

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:01:57.053449Z

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=pdf_text observed=2026-08-07T13:01:51.850585Z digest=sha256:19fcdfee95dca2a5dbc4db8a4e782af768e14b88b4ad2112acbdf4b73acf5702

Observation d9365125-da38-4b50-a6af-894b52ce8d58 · outbound

This paper cites Provably robust explainable graph neural networks against graph perturbation attacks.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Provably robust explainable graph neural networks against graph perturbation attacks

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:01:56.779336Z

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=pdf_text observed=2026-08-07T13:01:51.962646Z digest=sha256:6385fd2395a13b3b8b3752c7b5eb493e4ad58449b05f806cab6dab4821f17ebb

Observation f8655676-fa4c-4b33-a7ab-af25bf949ef4 · outbound

This paper cites Adversarial Examples on Graph Data: Deep Insights into Attack and Defense.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Adversarial Examples on Graph Data: Deep Insights into Attack and Defense

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-07T13:01:52.082536Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:01:52.082536Z digest=sha256:1879b2e4e5a73a950130b2c6a67b2c3463efd85504a833b7cd7e4b11b674c77d

Observation d8071f01-5b25-4cac-986d-380e670f81cd · outbound

This paper cites an unresolved cited work.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Unresolved cited work

Reference 34

Resolution
unresolved
raw_fallback, observed 2026-08-07T13:01:56.499188Z

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=pdf_text observed=2026-08-07T13:01:52.195897Z digest=sha256:913e087b178a5d854d2dff6700955da32babc7a46d47edf6558fa0f97ec10bf4

Observation 1867e828-460c-4cfe-8516-65e7161feb77 · outbound

This paper cites Optimal Inference in Contextual Stochastic Block Models.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Optimal Inference in Contextual Stochastic Block Models

Reference 35

Resolution
verified exact
local_arxiv, observed 2026-08-07T13:01:53.916976Z

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=pdf_text observed=2026-08-07T13:01:52.306985Z digest=sha256:d3d88e30eafeeb91bce18d9f3bfc5941da962428435b8779da009bf526a788d0

Observation b069ea1e-5310-4115-8e4d-a97f2ce023f9 · outbound

This paper cites Aegraph: Node attribute-enhanced graph encoder method.Expert Systems with Applications, 236:121382, 2024.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Aegraph: Node attribute-enhanced graph encoder method.Expert Systems with Applications, 236:121382, 2024

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:01:56.208407Z

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=pdf_text observed=2026-08-07T13:01:52.420470Z digest=sha256:aa331438bbdbf5f409d724b4a1e87f09afcb839d5cfb047b2b272780bac4cfc7

Observation 1eb34b7f-73c0-4157-bb17-b5c59307e4fc · outbound

This paper cites On the evolution of random graphs.Publ.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models On the evolution of random graphs.Publ

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T13:01:52.523012Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:01:52.523012Z digest=sha256:800c7a15e42ccd94e02d6054f12e48a425c74d8b38a6c2e5268fa8fa63cd2f16

Observation c660244d-7031-4a9f-a805-01ab1a81f34b · outbound

This paper cites Stochastic blockmodels: First steps.Social networks, 5(2):109–137, 1983.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Stochastic blockmodels: First steps.Social networks, 5(2):109–137, 1983

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T13:01:52.652117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:01:52.652117Z digest=sha256:708791254988af5b4e93eeb3c99b3ef4d0fa88350546318e928a35706dc74348

Observation 5355bb2a-7249-4ed9-bc81-1b084ab53302 · outbound

This paper cites Quantum chemistry structures and properties of 134 kilo molecules.Scientific data, 1(1):1–7, 2014.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Quantum chemistry structures and properties of 134 kilo molecules.Scientific data, 1(1):1–7, 2014

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T13:01:52.757529Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:01:52.757529Z digest=sha256:b59d98241a238335f484a5d88af4c84807c516ee96d8b30eb16113072d96b216

Observation d3a58f8c-3543-4085-bf9b-0f1e93fb0a95 · outbound

This paper cites Graph evolution: Densification and shrinking diameters.ACM transactions on Knowledge Discovery from Data (TKDD), 1(1):2–es, 2007.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Graph evolution: Densification and shrinking diameters.ACM transactions on Knowledge Discovery from Data (TKDD), 1(1):2–es, 2007

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T13:01:52.864154Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:01:52.864154Z digest=sha256:c6337638d0e621f39e44ddd0268c32c207378fe22f623bd0529d6c7c8c79bca2

Observation 16232ae7-081b-4572-a50e-b9336b08317d · outbound

This paper cites Large deviations for sums of partly dependent random variables.Random Structures & Algorithms, 24(3):234–248, 2004.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Large deviations for sums of partly dependent random variables.Random Structures & Algorithms, 24(3):234–248, 2004

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:01:55.915010Z

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=pdf_text observed=2026-08-07T13:01:52.986691Z digest=sha256:7943174205fdad609cd8d97669e28cf8dcd8cbd85e28590592326e00e0bbcf7c

Observation 0176d312-1631-40f8-9387-07b1f9f2826c · outbound

This paper cites an unresolved cited work.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Unresolved cited work

Reference 43

Resolution
unresolved
raw_fallback, observed 2026-08-07T13:01:55.680589Z

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=pdf_text observed=2026-08-07T13:01:53.129767Z digest=sha256:0a90636a721c8a1cef9bb24a6aae999776dc6e33d8a2fb212e896bc9afa47c28

Observation 2757d249-e47f-4aa5-866e-5927572ed9d7 · outbound

This paper cites This is first done by assuming a Beta conjugate prior to derive an exact analytical form for the variance.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models This is first done by assuming a Beta conjugate prior to derive an exact analytical form for the variance

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:01:55.399093Z

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=pdf_text observed=2026-08-07T13:01:53.267958Z digest=sha256:59a5849af7fb40e99036c6d3424d2c715eb45f9094c83412cd21d71b64ce0a24

Observation d52c4496-7cfa-4394-8abb-b9aabaf6132c · outbound

This paper cites sharp rate.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models sharp rate

Reference 45

Resolution
malformed identifier
raw_fallback, observed 2026-08-07T13:01:55.115815Z

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=pdf_text observed=2026-08-07T13:01:53.363678Z digest=sha256:d57727009ef399517c3a4f47448d756775b3c1e7f46952edf2f1c798646e0d8a

Observation 5446453f-fb7d-4a97-8a42-9064cf942f0d · outbound

This paper cites an unresolved cited work.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Unresolved cited work

Reference 2014

Resolution
verified exact
raw_fallback, observed 2026-08-07T13:01:54.318794Z

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=pdf_text observed=2026-08-07T13:01:51.739248Z digest=sha256:b5c62d18bc6bd924da74688daeb75cef18114403f147704a78b497974fe2a078

Pith citing papers

No inbound Pith citation observations are available.