DiGress: Discrete Denoising diffusion for graph generation | Paper Citation Record

Observation e5a23cc7-a32f-45fa-8f5a-d3e76471cf96 · inbound

xAI-Drop: Don't Use What You Cannot Explain cites this paper.

xAI-Drop: Don't Use What You Cannot Explain DiGress: Discrete Denoising diffusion for graph generation

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-23T23:03:34.628980Z

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Vertical Validation: Evaluating Implicit Generative Models for Graphs on Thin Support Regions cites this paper.

Vertical Validation: Evaluating Implicit Generative Models for Graphs on Thin Support Regions DiGress: Discrete Denoising diffusion for graph generation

Reference 12

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P2DFlow: A Protein Ensemble Generative Model with SE(3) Flow Matching cites this paper.

P2DFlow: A Protein Ensemble Generative Model with SE(3) Flow Matching DiGress: Discrete Denoising diffusion for graph generation

Reference 25

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Can Graph Neural Networks Learn Language with Extremely Weak Text Supervision? cites this paper.

Can Graph Neural Networks Learn Language with Extremely Weak Text Supervision? DiGress: Discrete Denoising diffusion for graph generation

Reference 14

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Observation 7aeda284-eede-42bb-8101-60ec94da1007 · inbound

Simple Guidance Mechanisms for Discrete Diffusion Models cites this paper.

Simple Guidance Mechanisms for Discrete Diffusion Models DiGress: Discrete Denoising diffusion for graph generation

Reference 26

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Observation d59f5011-28bd-4ad3-84ba-285be432a115 · inbound

Generative Adversarial Reviews: When LLMs Become the Critic cites this paper.

Generative Adversarial Reviews: When LLMs Become the Critic DiGress: Discrete Denoising diffusion for graph generation

Reference 27

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TrojFlow: Flow Models are Natural Targets for Trojan Attacks cites this paper.

TrojFlow: Flow Models are Natural Targets for Trojan Attacks DiGress: Discrete Denoising diffusion for graph generation

Reference 7

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Observation de6f8763-af29-49c9-b7f5-40d0ebd71a5f · inbound

FAP-CD: Fairness-Driven Age-Friendly Community Planning via Conditional Diffusion Generation cites this paper.

FAP-CD: Fairness-Driven Age-Friendly Community Planning via Conditional Diffusion Generation DiGress: Discrete Denoising diffusion for graph generation

Reference 33

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Observation d91cfa0d-f930-4bac-a245-4d90a5a74374 · inbound

Pharmacophore-guided de novo drug design with diffusion bridge cites this paper.

Pharmacophore-guided de novo drug design with diffusion bridge DiGress: Discrete Denoising diffusion for graph generation

Reference 17

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Observation 3b19083e-3c99-4a35-bf3a-98fc9101d4d1 · inbound

Graph Generative Pre-trained Transformer cites this paper.

Graph Generative Pre-trained Transformer DiGress: Discrete Denoising diffusion for graph generation

Reference 2017

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Observation dd454f91-6520-4830-9e3f-740858f94c0c · inbound

Generative AI Enabled Robust Sensor Placement in Cyber-Physical Power Systems: A Graph Diffusion Approach cites this paper.

Generative AI Enabled Robust Sensor Placement in Cyber-Physical Power Systems: A Graph Diffusion Approach DiGress: Discrete Denoising diffusion for graph generation

Reference 54

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Observation 922e2823-2ce4-4858-9148-2fabe1e13dae · inbound

Graph Defense Diffusion Model cites this paper.

Graph Defense Diffusion Model DiGress: Discrete Denoising diffusion for graph generation

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-23T04:52:34.239698Z

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Observation 128bc757-3941-4938-bfe2-ea53fc0b73de · inbound

Categorical Schr\"odinger Bridge Matching cites this paper.

Categorical Schr\"odinger Bridge Matching DiGress: Discrete Denoising diffusion for graph generation

Reference 62

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Observation c22c8a3d-2576-453a-b314-88cb9ac72820 · inbound

Do Graph Diffusion Models Accurately Capture and Generate Substructure Distributions? cites this paper.

Do Graph Diffusion Models Accurately Capture and Generate Substructure Distributions? DiGress: Discrete Denoising diffusion for graph generation

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-09T12:09:59.433936Z

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Observation 06dd4555-62ce-4838-9254-c6753cdadc98 · inbound

Theoretical Benefit and Limitation of Diffusion Language Model cites this paper.

Theoretical Benefit and Limitation of Diffusion Language Model DiGress: Discrete Denoising diffusion for graph generation

Reference 56

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Observation 7bffd98d-a779-4b86-ba97-c030e23986a3 · inbound

Satellites Reveal Mobility: A Commuting Origin-destination Flow Generator for Global Cities cites this paper.

Satellites Reveal Mobility: A Commuting Origin-destination Flow Generator for Global Cities DiGress: Discrete Denoising diffusion for graph generation

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-07T15:20:09.326789Z

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Observation d515951a-6e2c-4a4d-a3b4-a67f3cfd0526 · inbound

A Global Commuting Origin-Destination Flow Dataset for Urban Sustainable Development cites this paper.

A Global Commuting Origin-Destination Flow Dataset for Urban Sustainable Development DiGress: Discrete Denoising diffusion for graph generation

Reference 54

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Observation 6c310bf8-2c59-4649-8b8b-5592bb5c3704 · 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 DiGress: Discrete Denoising diffusion for graph generation

Reference 50

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Observation bcfa75b6-6537-4937-af54-fbe7eb05c77b · inbound

Graph Neural Networks in Modern AI-aided Drug Discovery cites this paper.

Graph Neural Networks in Modern AI-aided Drug Discovery DiGress: Discrete Denoising diffusion for graph generation

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-07T05:50:58.658384Z

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Observation 06992cab-fa3d-48ef-a4e0-7371f329df1d · inbound

A Deep Generative Model for the Simulation of Discrete Karst Networks cites this paper.

A Deep Generative Model for the Simulation of Discrete Karst Networks DiGress: Discrete Denoising diffusion for graph generation

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T04:44:57.427131Z

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Observation 8eecaf5b-dfc8-45ff-8788-c2b5bdc10b32 · 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 DiGress: Discrete Denoising diffusion for graph generation

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T21:21:13.733863Z

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Observation c089b52a-8fca-41a9-b3af-5fd7c59f61d1 · inbound

Non-exchangeable Conformal Prediction for Temporal Graph Neural Networks cites this paper.

Non-exchangeable Conformal Prediction for Temporal Graph Neural Networks DiGress: Discrete Denoising diffusion for graph generation

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-06T20:44:42.936745Z

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Observation 178beddd-79af-45f4-b26c-e75e0d35f705 · inbound

Graph Diffusion-Based AeBS Deployment and Resource Allocation in RSMA-Enabled URLLC Low-Altitude Wireless Networks cites this paper.

Graph Diffusion-Based AeBS Deployment and Resource Allocation in RSMA-Enabled URLLC Low-Altitude Wireless Networks DiGress: Discrete Denoising diffusion for graph generation

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T20:01:04.254852Z

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Observation 1df43017-957f-4751-962c-e2dc42d6d203 · inbound

GraphBrep: Learning B-Rep in Graph Structure for Efficient CAD Generation cites this paper.

GraphBrep: Learning B-Rep in Graph Structure for Efficient CAD Generation DiGress: Discrete Denoising diffusion for graph generation

Reference 36

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Observation d7502526-bb13-4906-83dc-8838c811272f · inbound

Semantically Consistent Discrete Diffusion for 3D Biological Graph Modeling cites this paper.

Semantically Consistent Discrete Diffusion for 3D Biological Graph Modeling DiGress: Discrete Denoising diffusion for graph generation

Reference 20

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Observation a1cd5714-a4a6-4c46-a6d8-cfc091161eca · inbound

DiffNMR: Diffusion Models for Nuclear Magnetic Resonance Spectra Elucidation cites this paper.

DiffNMR: Diffusion Models for Nuclear Magnetic Resonance Spectra Elucidation DiGress: Discrete Denoising diffusion for graph generation

Reference 28

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Observation 65d62021-ff28-4eb6-8a58-e0321ca392fe · inbound

Subgraph Generation for Generalizing on Out-of-Distribution Links cites this paper.

Subgraph Generation for Generalizing on Out-of-Distribution Links DiGress: Discrete Denoising diffusion for graph generation

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-06T17:10:48.918797Z

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Observation 0181e668-ede3-4d1a-bf0c-11c2025640ed · 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 DiGress: Discrete Denoising diffusion for graph generation

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-06T16:36:22.159952Z

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Observation 92224ec5-d63f-4fbe-9a9e-e1742b30096f · inbound

Beyond Interactions: Node-Level Graph Generation for Knowledge-Free Augmentation in Recommender Systems cites this paper.

Beyond Interactions: Node-Level Graph Generation for Knowledge-Free Augmentation in Recommender Systems DiGress: Discrete Denoising diffusion for graph generation

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-15T17:46:47.166031Z

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Observation 8f9301b7-b925-44f2-9b25-c2e172c6a133 · inbound

SpectraLLM: Uncovering the Ability of LLMs for Molecular Structure Elucidation from Multi-Spectral Data cites this paper.

SpectraLLM: Uncovering the Ability of LLMs for Molecular Structure Elucidation from Multi-Spectral Data DiGress: Discrete Denoising diffusion for graph generation

Reference 88

Resolution: metadata mismatch; arxiv_id, observed 2026-05-19T01:11:57.019734Z

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Observation 1a088320-1061-4010-a3ee-1814d023f0c3 · inbound

FlowMol3: Flow Matching for 3D De Novo Small-Molecule Generation cites this paper.

FlowMol3: Flow Matching for 3D De Novo Small-Molecule Generation DiGress: Discrete Denoising diffusion for graph generation

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-15T17:25:08.337074Z

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

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion cites this paper.

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

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Observation 4bd396fa-51c7-406c-9d8c-ab18e088a3bc · inbound

Multi-domain Distribution Learning for De Novo Drug Design cites this paper.

Multi-domain Distribution Learning for De Novo Drug Design DiGress: Discrete Denoising diffusion for graph generation

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-15T17:05:01.452738Z

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Observation 5ad16549-b85d-439b-809e-201285405b4f · 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 DiGress: Discrete Denoising diffusion for graph generation

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-05T16:00:39.595996Z

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Observation f46e3f5b-44b2-42c2-8af7-5a8f9ca11233 · inbound

GraphWeave: Interpretable and Robust Graph Generation via Random Walk Trajectories cites this paper.

GraphWeave: Interpretable and Robust Graph Generation via Random Walk Trajectories DiGress: Discrete Denoising diffusion for graph generation

Reference 17

Resolution: metadata mismatch; arxiv_id, observed 2026-05-18T14:01:27.157156Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 4c29bd8b-6977-4575-afbc-d0acc9d64bb5 · inbound

Efficient Inference for Coupled Hidden Markov Models in Continuous Time and Discrete Space cites this paper.

Efficient Inference for Coupled Hidden Markov Models in Continuous Time and Discrete Space DiGress: Discrete Denoising diffusion for graph generation

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-18T07:16:01.949327Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 2b75d532-0ae9-405c-8c3c-145aad91e33f · inbound

Discrete Bayesian Sample Inference for Graph Generation cites this paper.

Discrete Bayesian Sample Inference for Graph Generation DiGress: Discrete Denoising diffusion for graph generation

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-05-18T00:45:33.066603Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 8aaa78ae-6dfe-4e40-81b7-f337b8c55f37 · inbound

LangFlow: Continuous Diffusion Rivals Discrete in Language Modeling cites this paper.

LangFlow: Continuous Diffusion Rivals Discrete in Language Modeling DiGress: Discrete Denoising diffusion for graph generation

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-11T08:50:59.573908Z

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Observation 0fa435c8-613b-4088-93ba-c1c045340f9e · inbound

SynHAT: A Two-stage Coarse-to-Fine Diffusion Framework for Synthesizing Human Activity Traces cites this paper.

SynHAT: A Two-stage Coarse-to-Fine Diffusion Framework for Synthesizing Human Activity Traces DiGress: Discrete Denoising diffusion for graph generation

Reference 71

Resolution: verified exact; arxiv_id, observed 2026-05-10T11:35:18.790953Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation aff2e363-9a10-4ad5-b722-2f2a38814ee0 · inbound

Interpolating Discrete Diffusion Models with Controllable Resampling cites this paper.

Interpolating Discrete Diffusion Models with Controllable Resampling DiGress: Discrete Denoising diffusion for graph generation

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-10T06:46:37.467248Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 9c54a24b-e3e7-4bd5-9b25-3ad9b9e36205 · inbound

One Pass for All: A Discrete Diffusion Model for Knowledge Graph Triple Set Prediction cites this paper.

One Pass for All: A Discrete Diffusion Model for Knowledge Graph Triple Set Prediction DiGress: Discrete Denoising diffusion for graph generation

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-10T09:38:42.980462Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f62da919-c01d-42a5-8d1e-d9a0775df70d · inbound

GCCM: Enhancing Generative Graph Prediction via Contrastive Consistency Model cites this paper.

GCCM: Enhancing Generative Graph Prediction via Contrastive Consistency Model DiGress: Discrete Denoising diffusion for graph generation

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-11T19:31:08.932019Z

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Observation 6e6e9266-f30d-45cc-9e3a-49d542b9e772 · inbound

FlashMol: High-Quality Molecule Generation in as Few as Four Steps cites this paper.

FlashMol: High-Quality Molecule Generation in as Few as Four Steps DiGress: Discrete Denoising diffusion for graph generation

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-11T04:50:57.725536Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 69ba0ff5-3fee-4524-b27a-5bfb1f86fe2f · 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 DiGress: Discrete Denoising diffusion for graph generation

Reference 108

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T08:26:24.307304Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6deed3d3-261f-4670-8cde-e2dcab28e4c2 · inbound

Domain-Gated Latent Diffusion: Generative Inverse Design of HMX-Class Energetic Materials with First-Principles Validation cites this paper.

Domain-Gated Latent Diffusion: Generative Inverse Design of HMX-Class Energetic Materials with First-Principles Validation DiGress: Discrete Denoising diffusion for graph generation

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-07-01T16:55:50.503215Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 08b1d6fe-78d8-4f3c-856d-140c4efd967d · inbound

Adaptive Order Policies for Masked Diffusion cites this paper.

Adaptive Order Policies for Masked Diffusion DiGress: Discrete Denoising diffusion for graph generation

Reference 87

Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T23:42:49.839690Z

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Observation 1418030e-4dd0-4688-b19f-0521e4b5749a · inbound

Variational Learning for Insertion-based Generation cites this paper.

Variational Learning for Insertion-based Generation DiGress: Discrete Denoising diffusion for graph generation

Reference 39

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T22:26:17.760044Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b9ccc088-cb53-4569-b981-6f67e6b50a8a · inbound

Generative Molecular Morphing for Flexible-Size Design via Unbalanced Optimal Transport cites this paper.

Generative Molecular Morphing for Flexible-Size Design via Unbalanced Optimal Transport DiGress: Discrete Denoising diffusion for graph generation

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-07-02T16:17:09.006335Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 188dd33d-92f9-4a13-bc15-e6ee4c97d61a · inbound

Streamlining Analysis and Design of Two-Dimensional Electronic Spectroscopy using Machine Learning cites this paper.

Streamlining Analysis and Design of Two-Dimensional Electronic Spectroscopy using Machine Learning DiGress: Discrete Denoising diffusion for graph generation

Reference 194

Resolution: metadata mismatch; arxiv_id, observed 2026-06-26T19:29:48.138729Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 97413a29-d3ad-4f59-85d5-bd7f2b88787f · inbound

Interpretable Meta-Learning for Multi-Objective Chemical Search cites this paper.

Interpretable Meta-Learning for Multi-Objective Chemical Search DiGress: Discrete Denoising diffusion for graph generation

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-07-04T05:59:37.184715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 9934d899-3ce2-48f6-be6d-1a311db9196d · inbound

Modular Diffusion Models for Structured Visual Recognition cites this paper.

Modular Diffusion Models for Structured Visual Recognition DiGress: Discrete Denoising diffusion for graph generation

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-07-04T09:09:43.118769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 39f5e676-180f-4e38-8251-c6cb0ddeeb3c · inbound

Estimation-Prediction Tradeoff in Causal Probabilistic Temporal Graphs cites this paper.

Estimation-Prediction Tradeoff in Causal Probabilistic Temporal Graphs DiGress: Discrete Denoising diffusion for graph generation

Reference 257

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T17:05:50.454437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c0b130f7-6add-436a-aae2-742dcc7a86b7 · inbound

Accelerating Discrete Diffusion Models with Parallel-In-Time Sampling cites this paper.

Accelerating Discrete Diffusion Models with Parallel-In-Time Sampling DiGress: Discrete Denoising diffusion for graph generation

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-07-02T16:17:08.534161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d5843b15-732a-4624-8f0c-7de38d4a1c6d · inbound

Set Diffusion: Interpolating Token Orderings Between Autoregression and Diffusion for Fast and Flexible Decoding cites this paper.

Set Diffusion: Interpolating Token Orderings Between Autoregression and Diffusion for Fast and Flexible Decoding DiGress: Discrete Denoising diffusion for graph generation

Reference 79

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T17:38:43.640942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f59a465f-004f-433f-a072-75212c4f6538 · inbound

Symmetry-Structured Neural Completion of Islamic Geometric Patterns from Sparse Control Geometry cites this paper.

Symmetry-Structured Neural Completion of Islamic Geometric Patterns from Sparse Control Geometry DiGress: Discrete Denoising diffusion for graph generation

Reference 33

Resolution: unresolved; no resolver link, observed 2026-07-12T10:07:01.444366Z

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Graph Convolutional Attention: A Spectral Perspective on Graph Denoising and Diffusion cites this paper.

Graph Convolutional Attention: A Spectral Perspective on Graph Denoising and Diffusion DiGress: Discrete Denoising diffusion for graph generation

Reference 44

Resolution: verified exact; local_arxiv, observed 2026-07-11T00:07:41.986049Z

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CoDiffGRN: Rethinking Gene Regulatory Network Inference via the BEELINE-KGC Benchmark and Co-evolutionary Discrete Diffusion cites this paper.

CoDiffGRN: Rethinking Gene Regulatory Network Inference via the BEELINE-KGC Benchmark and Co-evolutionary Discrete Diffusion DiGress: Discrete Denoising diffusion for graph generation

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-02T06:19:08.446321Z

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Observation b37f7027-5952-49e4-91b2-2750b5af88e3 · inbound

Hierarchical Domain Generalization cites this paper.

Hierarchical Domain Generalization DiGress: Discrete Denoising diffusion for graph generation

Reference 146

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