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Paper Citation Record · LEDGER

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models

As of 15 August 2026, this Paper Citation Record lists 74 of 74 outbound references and 5 inbound Pith citation observations for arXiv:2506.00710.

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

pith.paper-citation-record.v1
2506.00710 v1

Coverage vector

measured 74 of 74 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:05:07.890501Z

measured 79 of 79 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T13:14:31.613157Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T22:27:26.237779Z

Reference resolution

74 of 74 outbound references displayed

  • verified exact2
  • verified fuzzy71
  • unresolved1
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0e25d6b8-8229-4483-bb13-56e3a8191d92 · outbound

This paper cites Differentially Private Synthetic Data Generation for Relational Databases.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Differentially Private Synthetic Data Generation for Relational Databases

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:10.523488Z

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=2026-08-07T12:05:07.375941Z digest=sha256:86d738de61bcfbd7e69426011a6ba30584c155ef667651e90bebbc5de7321759

Observation 4f23fa6e-9ee5-42d3-b339-b4e76cfe1229 · outbound

This paper cites Privacy and utility of private synthetic data for medical data analyses // Applied Sciences.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Privacy and utility of private synthetic data for medical data analyses // Applied Sciences

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:10.503960Z

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=2026-08-07T12:05:07.383591Z digest=sha256:e11fbb263b25f57bdb075c17515c76bea46c68092d2c6918f9ca9e71c3af0a46

Observation af5a8b7e-8c0b-4971-8851-1d731cc5cf28 · outbound

This paper cites Generating synthetic data in finance: opportunities, challenges and pitfalls // Proceedings of the First ACM International Conference on AI in Finance.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Generating synthetic data in finance: opportunities, challenges and pitfalls // Proceedings of the First ACM International Conference on AI in Finance

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:10.475747Z

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=2026-08-07T12:05:07.389562Z digest=sha256:6d82ec8794608d959ca5060d829ac86b018c425fa02a62aff1e87593ef39bb35

Observation 9746b5ad-ff2f-4dd8-b005-82a9d36d0807 · outbound

This paper cites Guide to the financial data set // PKDD2000 discovery challenge.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Guide to the financial data set // PKDD2000 discovery challenge

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:10.449999Z

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=2026-08-07T12:05:07.396612Z digest=sha256:9727f0147b3ab1991ff57c7ac28a1afa6dffa9c0784280ae78a919c2969c58c0

Observation 6ea71e17-b3cb-453c-acb5-fe2e31114f0f · outbound

This paper cites Experiments In Predicting Biodegradability // Applied Artificial Intelligence.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Experiments In Predicting Biodegradability // Applied Artificial Intelligence

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:10.428707Z

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=2026-08-07T12:05:07.401731Z digest=sha256:d27ed77cba41120de3b8f7f71c8332c4f570a7e4a15b91b128e2a46545e35ef4

Observation 1188c4ca-a84e-4b56-a6d5-547db56cedba · outbound

This paper cites Beyond Privacy: Navigating the Opportunities and Challenges of Synthetic Data.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Beyond Privacy: Navigating the Opportunities and Challenges of Synthetic Data

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:10.408860Z

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=2026-08-07T12:05:07.407572Z digest=sha256:a90fb683610246fcc8b722f302d9adea888aa559a1aa910b1730d162c8947b71

Observation 4a4ccfae-4a4f-422a-81f3-881db6e876e3 · outbound

This paper cites Position: Why Tabular Foundation Models Should Be a Research Priority // Forty-first International Conference on Machine Learning.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Position: Why Tabular Foundation Models Should Be a Research Priority // Forty-first International Conference on Machine Learning

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:10.388604Z

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=2026-08-07T12:05:07.417045Z digest=sha256:bfe975113e2eef5690375f87fb76e4b412a4d8a271463adcc01c90dcaa131845

Observation e988d764-dcd8-46c0-b185-c5e79b3add92 · outbound

This paper cites PrivLava: Synthesizing Relational Data with Foreign Keys under Differential Privacy // Proc.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models PrivLava: Synthesizing Relational Data with Foreign Keys under Differential Privacy // Proc

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:10.367163Z

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=2026-08-07T12:05:07.421964Z digest=sha256:d6b0d036d239b2a03349b5a31f2de2a5a5606e2f2b8074fe76c70a59163c7444

Observation 0e82ab22-4954-41de-9f18-249b723f1831 · outbound

This paper cites PrivPetal: Relational Data Synthesis via Permutation Relations.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models PrivPetal: Relational Data Synthesis via Permutation Relations

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:10.346423Z

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=2026-08-07T12:05:07.431683Z digest=sha256:0957e44fff833a0999f96394847a29ce1d549ba014a4f97201b52d9937a06fec

Observation adee922c-7c77-47b7-b73a-364af0d54fcf · outbound

This paper cites SMOTE: synthetic minority over-sampling technique // Journal of artificial intelligence research.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models SMOTE: synthetic minority over-sampling technique // Journal of artificial intelligence research

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:10.325655Z

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=2026-08-07T12:05:07.436816Z digest=sha256:b8512c772577399bea15a19916f5e07a546c2d098705920766dd0aead1edaf92

Observation 18d8d387-cb2b-471a-bb09-ff7e9ef4b4a6 · outbound

This paper cites A relational model of data for large shared data banks // Communications of the ACM.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models A relational model of data for large shared data banks // Communications of the ACM

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:10.303810Z

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=2026-08-07T12:05:07.451978Z digest=sha256:3a5b6cd5353dff461b221f85a11a5713cff199ec07ec916d2c6ab3d7beea5456

Observation 141b4aa7-2ca2-49e6-af9a-cd260caf437a · outbound

This paper cites DBMS popularity broken down by database model.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models DBMS popularity broken down by database model

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:10.281319Z

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=2026-08-07T12:05:07.461334Z digest=sha256:e983c33dcd572dd5623e76662d604ad6544f92838f21d87d01319c5db22d5e08

Observation 01c77302-a81b-4371-9a0c-0fb5abfd6caa · outbound

This paper cites Spectral analysis of random graphs with skewed degree distributions // 45th Annual IEEE Symposium on Foundations of Computer Science.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Spectral analysis of random graphs with skewed degree distributions // 45th Annual IEEE Symposium on Foundations of Computer Science

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:10.258063Z

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=2026-08-07T12:05:07.472919Z digest=sha256:c1f02c596772009b50de3371e40e356e2b6d398255ecd32082e836cc21425c53

Observation b63142e6-8aab-4716-8385-1db671668bb1 · outbound

This paper cites Normalization and hierarchical dependencies in the relational data model // ACM Transactions on Database Systems (TODS).

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Normalization and hierarchical dependencies in the relational data model // ACM Transactions on Database Systems (TODS)

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:10.237346Z

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=2026-08-07T12:05:07.483588Z digest=sha256:171ddc8e9cf706f15ba50119db9f1f767f4780204e260c8298b890214c23ee14

Observation e9f76cb7-ea69-4592-8dd8-c7473b71579b · outbound

This paper cites Position: relational deep learning-graph representation learning on relational databases // Proceedings of the 41st International Conference on Machine Learning.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Position: relational deep learning-graph representation learning on relational databases // Proceedings of the 41st International Conference on Machine Learning

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:10.217948Z

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=2026-08-07T12:05:07.493107Z digest=sha256:b932e4efb6198273bc0a2ff0bc565ed92401f034d22232300f15431520ffcdd8

Observation f1c7ba1c-2e24-4ccd-8147-6323b7aed1a1 · outbound

This paper cites Rossmann Store Sales.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Rossmann Store Sales

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:10.196967Z

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=2026-08-07T12:05:07.501524Z digest=sha256:01764d1e23e717acd28122a7b9c45561e8d0121759e04040ea7059aacae4f17e

Observation 4f2038cc-64e1-4c43-98ec-1be5a9879379 · outbound

This paper cites Tabular and latent space synthetic data generation: a literature review // Journal of Big Data.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Tabular and latent space synthetic data generation: a literature review // Journal of Big Data

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:10.165555Z

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=2026-08-07T12:05:07.507139Z digest=sha256:ed5e41010a82ece588426d721c6182fd9eb840cba9b4cd5e4ae8a2c97889d6c6

Observation 5325984c-3ef6-4f53-a414-0cbc0fa478f9 · outbound

This paper cites Learning probabilistic relational models // IJCAI.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Learning probabilistic relational models // IJCAI

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:10.140055Z

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=2026-08-07T12:05:07.512619Z digest=sha256:fc403311f3dbf1473af0e93f51f10d699614daace6a4a03d3989a12904b5979f

Observation 774543f8-6166-4b50-9a65-77d20045868a · outbound

This paper cites Database systems: the complete book.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Database systems: the complete book

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:10.118872Z

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=2026-08-07T12:05:07.519230Z digest=sha256:7a8d866ed5f73bca47e1eb28f6bfe3866c3509e16f5ab28f7a3d6aaca9c8aed2

Observation 1f99ceed-c540-4167-b98d-4832d6afeac8 · outbound

This paper cites KAMINO: Constraint-aware differentially private data synthesis // Proceedings of the VLDB Endowment.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models KAMINO: Constraint-aware differentially private data synthesis // Proceedings of the VLDB Endowment

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:10.089455Z

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=2026-08-07T12:05:07.526137Z digest=sha256:f95af5dd756710792d1286ef1e7638529b6680332cc9429a47343c821ca72331

Observation 2e535c5a-d249-449d-a2a9-e8ea2c7c0887 · outbound

This paper cites Learning probabilistic relational models // Relational data mining.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Learning probabilistic relational models // Relational data mining

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:10.066320Z

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=2026-08-07T12:05:07.532991Z digest=sha256:51d110f0499dfe52bfdaad8b59c0237c60c848f5c69900fe874891043b0c4f4f

Observation a8c4a1e3-5998-4a36-a86a-92d01d280233 · outbound

This paper cites Differentially private data release over multiple tables // Proceedings of the 42nd ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Differentially private data release over multiple tables // Proceedings of the 42nd ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:10.041590Z

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=2026-08-07T12:05:07.541096Z digest=sha256:dfb0e61720ccdede65368db0b26f971837427225e40f890bf395ed41e412d068

Observation 12cfa1cc-b9bd-4865-a35e-388201e103d0 · outbound

This paper cites Synthetic data in health care: A narrative review // PLOS Digital Health.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Synthetic data in health care: A narrative review // PLOS Digital Health

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:10.020770Z

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=2026-08-07T12:05:07.549266Z digest=sha256:9eff2ad7fe5e5f0733de44e538de6854fc757443e6d983c11789c43927a83242

Observation b2089ac6-f068-4598-b468-8d5bc11a87cf · outbound

This paper cites Row Conditional-TGAN for generating synthetic relational databases // ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Row Conditional-TGAN for generating synthetic relational databases // ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:09.998682Z

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=2026-08-07T12:05:07.555858Z digest=sha256:ac4251b395bfdc94c3c832ea732d278e773b6259981064a65a6180c53bfb6e60

Observation 406fd319-d16d-4f6a-a052-6c03f688b5cb · outbound

This paper cites Inductive representation learning on large graphs // Advances in neural information processing systems.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Inductive representation learning on large graphs // Advances in neural information processing systems

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:09.975816Z

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=2026-08-07T12:05:07.567630Z digest=sha256:61c5cfc69ce62ff9c7f25d68595440b9a9ce3879bb14280d98495e77e3bc1c6d

Observation a18f849f-bcea-4e61-8b2c-76dd39b63664 · outbound

This paper cites Reimagining synthetic tabular data generation through data-centric AI: A comprehensive benchmark // Advances in neural information processing systems.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Reimagining synthetic tabular data generation through data-centric AI: A comprehensive benchmark // Advances in neural information processing systems

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:09.950295Z

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=2026-08-07T12:05:07.572813Z digest=sha256:2fb98fa31b4f0ff8ac6c07fe5eafc760a15d141214c134c86c44bb0a96eecbbd

Observation 9b9f006b-c9b2-4099-baec-f413b99de4c8 · outbound

This paper cites Maxwell, Konstan Joseph A.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Maxwell, Konstan Joseph A

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:09.928060Z

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=2026-08-07T12:05:07.578947Z digest=sha256:23e76741c383026ea57aad395dad84dba7dac141acc1aef0795fe778524e9f66

Observation 5217797f-8d38-42e8-80aa-8f9ceea2f1d5 · outbound

This paper cites Synthetic data generation for tabular health records: A systematic review // Neurocomputing.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Synthetic data generation for tabular health records: A systematic review // Neurocomputing

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:09.891129Z

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=2026-08-07T12:05:07.584376Z digest=sha256:c2c73e5822fc704bf4393ca55cd2c6edc0eafaf98349241dae68e65d6edc6ba5

Observation 49aa07e7-cbba-4b69-ac8c-e6352e16a5e7 · outbound

This paper cites Stochastic blockmodels: First steps // Social networks.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Stochastic blockmodels: First steps // Social networks

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:09.857457Z

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=2026-08-07T12:05:07.589650Z digest=sha256:80a8044fda2cc90294854425d622010425dbfa9d2c58a62f86f8bc2625edeef3

Observation a6843f0b-d229-44d3-b382-5e35e192ff2f · outbound

This paper cites Relational Data Generation with Graph Neural Networks and Latent Diffusion Models // NeurIPS 2024 Third Table Representation Learning Workshop.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Relational Data Generation with Graph Neural Networks and Latent Diffusion Models // NeurIPS 2024 Third Table Representation Learning Workshop

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:09.830226Z

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=2026-08-07T12:05:07.594800Z digest=sha256:7271dade243b57dd73452f53da0b73f0903c8573b01fb980e0b3512c7100c723

Observation fe42d954-ea22-4e3b-8841-1010d342b542 · outbound

This paper cites Benchmarking the Fidelity and Utility of Synthetic Relational Data.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Benchmarking the Fidelity and Utility of Synthetic Relational Data

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:09.809781Z

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=2026-08-07T12:05:07.603991Z digest=sha256:d47e40a8ffa840aa6d976677738d4defdb03bcc57daf6e2e3bc18db0f25f1ba0

Observation 7e1814ed-ec3f-46bb-9c83-8c916db1e16e · outbound

This paper cites A Simple and Scalable Representation for Graph Generation // The Twelfth International Conference on Learning Representations.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models A Simple and Scalable Representation for Graph Generation // The Twelfth International Conference on Learning Representations

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:09.783656Z

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=2026-08-07T12:05:07.619304Z digest=sha256:8e31a43c2eadd85ef1e39b5dad211ecf738b77e17f300bf7ca32e6b1ef5e5c20

Observation aa9010ce-70a4-4d84-af85-f9891d6ba8d2 · outbound

This paper cites SyntheRela: A Benchmark For Synthetic Relational Database Generation // Will Synthetic Data Finally Solve the Data Access Problem? 2025.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models SyntheRela: A Benchmark For Synthetic Relational Database Generation // Will Synthetic Data Finally Solve the Data Access Problem? 2025

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:09.747840Z

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=2026-08-07T12:05:07.630860Z digest=sha256:090c720800fc3d170b030c18163ab6deb75de1866a1e779d57ca6fa6dd98a731

Observation 0771bcf6-17ee-4c55-bb9b-9ac00160ca96 · outbound

This paper cites Synthesizing Accurate Relational Data under Differential Privacy // 2024 IEEE International Conference on Big Data (BigData).

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Synthesizing Accurate Relational Data under Differential Privacy // 2024 IEEE International Conference on Big Data (BigData)

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:09.545939Z

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=2026-08-07T12:05:07.639269Z digest=sha256:6b87bbc32c24d091a4293adbe0587d3d541f5c984e57039fbcbd942fb9b6efc3

Observation ca1444e2-339c-4542-a301-6e389ed5b3df · outbound

This paper cites Elucidating the Design Space of Diffusion-Based Generative Models // Advances in Neural Information Processing Systems.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Elucidating the Design Space of Diffusion-Based Generative Models // Advances in Neural Information Processing Systems

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:09.524794Z

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=2026-08-07T12:05:07.645974Z digest=sha256:a133102df31aac2b5e8a42a847f865a1946834408cb51d91c42dc8f99d44fba5

Observation 013d1c62-39c5-4d0f-989d-ad38ba8b90a4 · outbound

This paper cites Variational Diffusion Models // Advances in Neural Information Processing Systems.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Variational Diffusion Models // Advances in Neural Information Processing Systems

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:09.494584Z

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=2026-08-07T12:05:07.654928Z digest=sha256:8b455e8dd4e398e159ed70ddf684a70a10d10ee1b707e951870b6ca86ed10a68

Observation 02f81959-521c-4fde-a4e7-cb563f4ff28c · outbound

This paper cites Tabddpm: Modelling tabular data with diffusion models // International Conference on Machine Learning.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Tabddpm: Modelling tabular data with diffusion models // International Conference on Machine Learning

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:09.462214Z

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=2026-08-07T12:05:07.662144Z digest=sha256:522904f51f8e10297470dc39b116ddc83d40818250d2065818562e49ea659870

Observation 01e0644a-b5ec-4788-ae8e-0041ed3da121 · outbound

This paper cites IRG: Generating Synthetic Relational Databases using GANs // arXiv preprint arXiv:2312.15187.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models IRG: Generating Synthetic Relational Databases using GANs // arXiv preprint arXiv:2312.15187

Reference 38

Resolution
verified exact
raw_fallback, observed 2026-08-07T12:05:08.270431Z

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=2026-08-07T12:05:07.669471Z digest=sha256:1601b795e294e4700eccd90c9b31ec72db1b73939bd5377a6e22294f15acbcc4

Observation 5a98b6dd-59cc-41cb-ac3e-15edfc52d9c3 · outbound

This paper cites GraphMaker: Can Diffusion Models Generate Large Attributed Graphs? // Transactions on Machine Learning Research.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models GraphMaker: Can Diffusion Models Generate Large Attributed Graphs? // Transactions on Machine Learning Research

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:09.431690Z

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=2026-08-07T12:05:07.679590Z digest=sha256:f967dcc848409b3f2ba8781ae1ba4b42f7ae15941bf5cbfeca718ebf82e094ab

Observation fbfd1e8a-f784-49d5-b753-93d45e65f014 · outbound

This paper cites Efficient graph generation with graph recurrent attention networks // Advances in neural information processing systems.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Efficient graph generation with graph recurrent attention networks // Advances in neural information processing systems

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:09.398112Z

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=2026-08-07T12:05:07.686020Z digest=sha256:b9160d0e56d98e46c976ea7cc45796507e3b6362a0e4311b50360677ee4676ff

Observation 3bc429cd-abd0-4904-a3e4-3ff83686749a · outbound

This paper cites Graph normalizing flows // Advances in Neural Information Processing Systems.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Graph normalizing flows // Advances in Neural Information Processing Systems

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:09.363664Z

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=2026-08-07T12:05:07.692737Z digest=sha256:6ebf68e8bf970f16e0f49de4bdc6f7ad7644e3308e433db2fbda4097fb73ae21

Observation d3fb7672-5968-41a1-bdf7-729d0caec550 · outbound

This paper cites an unresolved cited work.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Unresolved cited work

Reference 42

Resolution
verified exact
doi, observed 2026-08-07T12:05:07.944777Z

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=2026-08-07T12:05:07.697714Z digest=sha256:5d9be29834424fe42d2c69b5b6f2fe7b362726404fb2ff279d2747531e212826

Observation c10487de-c9d9-4e21-9c5b-bb7ade35384f · outbound

This paper cites Systematic topology analysis and generation using degree correlations // ACM SIGCOMM Computer Communication Review.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Systematic topology analysis and generation using degree correlations // ACM SIGCOMM Computer Communication Review

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:09.331321Z

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=2026-08-07T12:05:07.704847Z digest=sha256:42bfaf16a357531a53c46cd60cee13653acbeb4c9e7ce147b991039261917fd3

Observation f0d5769b-e54d-4298-80ed-b88ef0dd7fc8 · outbound

This paper cites Generating Realistic Synthetic Relational Data through Graph Variational Autoencoders // NeurIPS 2022 Workshop on Synthetic Data for Empowering ML Research.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Generating Realistic Synthetic Relational Data through Graph Variational Autoencoders // NeurIPS 2022 Workshop on Synthetic Data for Empowering ML Research

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:09.302132Z

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=2026-08-07T12:05:07.717390Z digest=sha256:e2e31ff3512753796bb880e429f733198f6a654ac8046bab3815fce27b81a6f4

Observation 6363e0dd-468c-4b67-be2b-9085b1713529 · outbound

This paper cites Automating the construction of internet portals with machine learning // Information Retrieval.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Automating the construction of internet portals with machine learning // Information Retrieval

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:09.271205Z

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=2026-08-07T12:05:07.724348Z digest=sha256:d79f674844f9586765879d2867aa1a00a046d571eb764d7cdda13c5d7ebcb311

Observation b3a18ed8-71d2-4ee5-81c8-451039820889 · outbound

This paper cites AIM: an adaptive and iterative mechanism for differentially private synthetic data // Proceedings of the VLDB Endowment.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models AIM: an adaptive and iterative mechanism for differentially private synthetic data // Proceedings of the VLDB Endowment

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:09.203017Z

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=2026-08-07T12:05:07.730452Z digest=sha256:177cc2c4256b365ae312c0c5e2a880b5de748459a1384534b6735f5960cdf337

Observation e2a53019-9644-44d2-8e0e-41c716192cf3 · outbound

This paper cites Airbnb New User Bookings.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Airbnb New User Bookings

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:09.170008Z

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=2026-08-07T12:05:07.735805Z digest=sha256:7c173df164931998de77ed60e11f3513559eff78d074fcab73311458cc4118aa

Observation d28ebc76-d852-4498-99b0-97316a9921f6 · outbound

This paper cites The CTU Prague Relational Learning Repository.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models The CTU Prague Relational Learning Repository

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-07T12:05:07.741940Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:05:07.741940Z digest=sha256:0906efca8fbe7ad24c2010fc24e6286d42488a6ae4342ff152c5f80647e7fae3

Observation 42688397-008f-4fe8-ba1d-78b804716bfd · outbound

This paper cites Bias in data-driven artificial intelligence systems—An introductory survey // Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Bias in data-driven artificial intelligence systems—An introductory survey // Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:09.145315Z

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=2026-08-07T12:05:07.748640Z digest=sha256:6fac611338045b715e4977a3417d002c313a5a2c0b8f2699c0af2f66d116c76c

Observation a9525d0b-520d-4712-9fcf-f7d760136b29 · outbound

This paper cites Clava DDPM : Multi-relational Data Synthesis with Cluster-guided Diffusion Models // The Thirty-eighth Annual Conference on Neural Information Processing Systems.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Clava DDPM : Multi-relational Data Synthesis with Cluster-guided Diffusion Models // The Thirty-eighth Annual Conference on Neural Information Processing Systems

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:09.108883Z

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=2026-08-07T12:05:07.753396Z digest=sha256:d265d3d452ba3411db068cef5db440affe0c23f9bd9195df8b74cfa638f59914

Observation 5591fc13-f581-456c-a184-a02a9c5b4c2f · outbound

This paper cites The Synthetic Data Vault // 2016 IEEE International Conference on Data Science and Advanced Analytics (DSAA).

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models The Synthetic Data Vault // 2016 IEEE International Conference on Data Science and Advanced Analytics (DSAA)

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:09.053403Z

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=2026-08-07T12:05:07.759030Z digest=sha256:2c6979a086d40534d191471e23f5b391f13ad9b3f3c76959aba8cc911aaeb5ae

Observation 2e572633-a38f-42f5-a8f3-c8c01c65b905 · outbound

This paper cites Hierarchical block structures and high-resolution model selection in large networks // Physical Review X.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Hierarchical block structures and high-resolution model selection in large networks // Physical Review X

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:09.028773Z

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=2026-08-07T12:05:07.764084Z digest=sha256:d451f17fa4c2befd82a1e8b974f4c10c9f4da5159aa0c2b1c3b7692196d12f0c

Observation c4a4b980-1612-488a-8978-2019527395f2 · outbound

This paper cites Nonparametric Bayesian inference of the microcanonical stochastic block model // Physical Review E.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Nonparametric Bayesian inference of the microcanonical stochastic block model // Physical Review E

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:09.000276Z

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=2026-08-07T12:05:07.769209Z digest=sha256:1e82f44eed8c07b5278a8f764f14042b341c53c36b777512a56bf073ade46f7f

Observation 32310c26-e221-4af8-bd3f-7c04acd22192 · outbound

This paper cites Bayesian stochastic blockmodeling // Advances in network clustering and blockmodeling.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Bayesian stochastic blockmodeling // Advances in network clustering and blockmodeling

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:08.938671Z

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=2026-08-07T12:05:07.774888Z digest=sha256:f9bc21c5a79c61a683570dfd822c772f7ffc30eea1d0078a14990390856d33a5

Observation 5cd2bb2e-737a-4ba4-ab38-63fa24bbb93d · outbound

This paper cites Synthetic Data Applications in Finance.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Synthetic Data Applications in Finance

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:08.903667Z

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=2026-08-07T12:05:07.782102Z digest=sha256:097218311c1f6192877ecf04313fd3c64730386bc998d2278c29f3f0e084e55f

Observation b1286917-10f6-4192-9dfc-a32902b7d76a · outbound

This paper cites Synthetic data // Annual review of statistics and its application.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Synthetic data // Annual review of statistics and its application

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:08.871672Z

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=2026-08-07T12:05:07.787654Z digest=sha256:94e5182830ef5f40c4d8d665d735825b6361dab4527d94b089ab334ad04ebbc2

Observation 386aca3c-733e-486c-b428-6621a74b074d · outbound

This paper cites RelBench: A Benchmark for Deep Learning on Relational Databases.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models RelBench: A Benchmark for Deep Learning on Relational Databases

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:08.842229Z

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=2026-08-07T12:05:07.792628Z digest=sha256:792690d3644f1dbec5e952fc887c1fb185a8fe6872c04689786a73b2eccc7c91

Observation 722d9bc6-aa6b-46d6-98c4-874153c51c6d · outbound

This paper cites Simple and Effective Masked Diffusion Language Models // The Thirty-eighth Annual Conference on Neural Information Processing Systems.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Simple and Effective Masked Diffusion Language Models // The Thirty-eighth Annual Conference on Neural Information Processing Systems

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:08.805741Z

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=2026-08-07T12:05:07.797265Z digest=sha256:b47239c3c3e810adc90c349b80bd6b3d8a8c2002f386f5732392d719691f8068

Observation 3174df81-aa5b-4916-9730-0a7463cbcc77 · outbound

This paper cites TabDiff: a Mixed-type Diffusion Model for Tabular Data Generation // The Thirteenth International Conference on Learning Representations.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models TabDiff: a Mixed-type Diffusion Model for Tabular Data Generation // The Thirteenth International Conference on Learning Representations

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:08.773324Z

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=2026-08-07T12:05:07.801480Z digest=sha256:aa106b306bbb2f84bedffac10de26049fda61b4ba3b42de3202b452ba322bb31

Observation e1afd093-a321-49b7-b324-d4de60db5227 · outbound

This paper cites REaLTabFormer: Generating Realistic Relational and Tabular Data using Transformers.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models REaLTabFormer: Generating Realistic Relational and Tabular Data using Transformers

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:08.734344Z

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=2026-08-07T12:05:07.807509Z digest=sha256:bac0c4e8026d004bf185572f18b0c845ed06ef48929e4cc596674854404dbd81

Observation b3f7216b-2621-4701-80d9-84fb5deef810 · outbound

This paper cites Instacart Market Basket Analysis.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Instacart Market Basket Analysis

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:08.697748Z

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=2026-08-07T12:05:07.813193Z digest=sha256:6883e5037d4263e2ea9d3338220436829d347f4556eb75a4d91406cfec3bd627

Observation deff8baf-fb45-4a9e-8808-c2940259f28e · outbound

This paper cites 2k+ graph construction framework: Targeting joint degree matrix and beyond // IEEE/ACM Transactions on Networking.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models 2k+ graph construction framework: Targeting joint degree matrix and beyond // IEEE/ACM Transactions on Networking

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:08.655142Z

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=2026-08-07T12:05:07.818049Z digest=sha256:f4214086efc0bc8a8a1d2b1a7d89663f3965e99acf3b11b7c9b81c8a48fc8e1e

Observation 91fc49df-e487-4afc-aca3-c7a9aa443a08 · outbound

This paper cites TabularARGN: A Flexible and Efficient Auto-Regressive Framework for Generating High-Fidelity Synthetic Data.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models TabularARGN: A Flexible and Efficient Auto-Regressive Framework for Generating High-Fidelity Synthetic Data

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:08.611677Z

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=2026-08-07T12:05:07.823383Z digest=sha256:862fd73a8e880a4067b2770d01348452f91e9469dd787e26fe1add323f627a58

Observation 6cee360a-1273-42d7-a07e-af5b7870167d · outbound

This paper cites DiGress: Discrete Denoising diffusion for graph generation // The Eleventh International Conference on Learning Representations.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models DiGress: Discrete Denoising diffusion for graph generation // The Eleventh International Conference on Learning Representations

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:08.581718Z

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=2026-08-07T12:05:07.828144Z digest=sha256:68f22fb9ad796fe2a7915e9fa6f8bfe31e28230e6887066e611b902784f76903

Observation a045ed11-31df-408a-9b4c-11b6ebf9d535 · outbound

This paper cites Walmart Recruiting - Store Sales Forecasting.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Walmart Recruiting - Store Sales Forecasting

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:08.554801Z

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=2026-08-07T12:05:07.833212Z digest=sha256:d299abdc8fae5309a49303d8d0d23b9c05a4d22f456eb6b766826d7074a11114

Observation 7f5b936b-81e8-45eb-9feb-b765f6d0a0ac · outbound

This paper cites Synthetic Data Generation of Many-to-Many Datasets via Random Graph Generation // The Eleventh International Conference on Learning Representations.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Synthetic Data Generation of Many-to-Many Datasets via Random Graph Generation // The Eleventh International Conference on Learning Representations

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:08.523042Z

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=2026-08-07T12:05:07.838604Z digest=sha256:36051606a034c9a8fb003ac7f96af204ebb2447fa17e55866135315c25ec209c

Observation e5a77fa8-0340-4ec2-ac5e-b6e446164db3 · outbound

This paper cites Modeling tabular data using conditional gan // Advances in neural information processing systems.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Modeling tabular data using conditional gan // Advances in neural information processing systems

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:08.500686Z

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=2026-08-07T12:05:07.844039Z digest=sha256:1a346dd2b067464a7db6873f49e9d454d898e1e647ddc26be674eb17ae4beaf8

Observation 614ce4cc-fc6b-44a1-a16d-e5061de02d02 · outbound

This paper cites Handling missing data with graph representation learning // Advances in Neural Information Processing Systems.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Handling missing data with graph representation learning // Advances in Neural Information Processing Systems

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:08.478108Z

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=2026-08-07T12:05:07.850865Z digest=sha256:306ebcd7d834781211016575f3defa78332572b031cdfbca47262dbe2ad27fff

Observation 6625768b-516b-4aac-8e06-10b41d318759 · outbound

This paper cites Graphrnn: Generating realistic graphs with deep auto-regressive models // International conference on machine learning.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Graphrnn: Generating realistic graphs with deep auto-regressive models // International conference on machine learning

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:08.450944Z

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=2026-08-07T12:05:07.858015Z digest=sha256:9a2c4094ca621614462cafee19f553f1f22bdf170a403151d6767d03551b1c4c

Observation 356e6734-2cf7-4ee4-89f6-c73be427c06c · outbound

This paper cites Tabular Data Generation: Can We Fool XGB oost ? // NeurIPS 2022 First Table Representation Workshop.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Tabular Data Generation: Can We Fool XGB oost ? // NeurIPS 2022 First Table Representation Workshop

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:08.420947Z

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=2026-08-07T12:05:07.865187Z digest=sha256:d629fe779a4f566a3337cf8c7afa6d1a8539eb3f6493498344c8db49dbb4222f

Observation 13344d47-a578-4114-868b-e69ddf9cb2e4 · outbound

This paper cites DiffPuter: An EM -Driven Diffusion Model for Missing Data Imputation // The Thirteenth International Conference on Learning Representations.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models DiffPuter: An EM -Driven Diffusion Model for Missing Data Imputation // The Thirteenth International Conference on Learning Representations

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:08.389539Z

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=2026-08-07T12:05:07.872261Z digest=sha256:d2d225686a96ba6a7c5e7d97c40975699c021d599b1e66ff209b420bcd18e4f2

Observation 145abe06-4219-4885-8eaf-0ff2a8bcb610 · outbound

This paper cites Mixed-Type Tabular Data Synthesis with Score-based Diffusion in Latent Space // The Twelfth International Conference on Learning Representations.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Mixed-Type Tabular Data Synthesis with Score-based Diffusion in Latent Space // The Twelfth International Conference on Learning Representations

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:08.365231Z

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=2026-08-07T12:05:07.878060Z digest=sha256:d8c98b2ffbdd388e85205a668e17e32aea36ba0f8666b181a03b2fcd7a0a2bb2

Observation 0446e6cd-cf20-4bcb-b9e3-2fc8376ccc2e · outbound

This paper cites Privbayes: Private data release via bayesian networks // ACM Transactions on Database Systems (TODS).

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Privbayes: Private data release via bayesian networks // ACM Transactions on Database Systems (TODS)

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:08.323279Z

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=2026-08-07T12:05:07.884162Z digest=sha256:8cb84eef50a9e75400372c7d70e6f238c3ddf2f3645e9639708af7812850cfdc

Observation 03657228-3e82-416f-aa1f-237e2bd0afa9 · outbound

This paper cites Ctab-gan: Effective table data synthesizing // Asian Conference on Machine Learning.

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models Ctab-gan: Effective table data synthesizing // Asian Conference on Machine Learning

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:05:08.295466Z

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=2026-08-07T12:05:07.890501Z digest=sha256:49fddc88f3223535d8a14b9f570e36c63ba7e0fe9c4e4ac7f765737e8843748f

Pith citing papers

Observation d1394855-e93f-4f86-b7f0-5d5317d59998 · inbound

RelBench v2: A Large-Scale Benchmark and Repository for Relational Data cites this paper.

RelBench v2: A Large-Scale Benchmark and Repository for Relational Data RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-16T02:02:06.839332Z

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=pdf_text observed=2026-05-16T02:01:21.704891Z digest=sha256:602e2b7f3124b2ab1e5c8af7729d33f461a1395969c11a8aa2bc496bd6830b32

Observation c73510ae-4749-44b8-b709-a470e6671101 · inbound

Declarative Outcome-Conformant Synthesis: Exact, Closed-Form Specification Satisfaction and a Conformance Benchmark cites this paper.

Declarative Outcome-Conformant Synthesis: Exact, Closed-Form Specification Satisfaction and a Conformance Benchmark RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-07-02T22:27:26.240470Z

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=pdf_text observed=2026-06-27T18:52:00.562764Z digest=sha256:93e6003c58325caf6d8a0d9bb628c7796d103ed81c095078e0ffc2f969404d57

Observation af122ea4-4ff2-443b-8b1f-e6ffffdaa919 · inbound

Sequential RC-TGAN: Generating Relational Time Series with Spectral Envelope Loss cites this paper.

Sequential RC-TGAN: Generating Relational Time Series with Spectral Envelope Loss RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models

Reference 10

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T06:35:29.319614Z

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=pdf_text observed=2026-07-01T06:35:06.822132Z digest=sha256:50ba3c92bb415d10c707b60fd32ae8c6ec1aea22eefc202a105d56a3b1202a72

Observation 8ad00faa-9c84-44f2-88e0-06f8b07f16b3 · inbound

Seq2Synth: Benchmarking Temporal Fidelity in Synthetic Sequential Tabular Data cites this paper.

Seq2Synth: Benchmarking Temporal Fidelity in Synthetic Sequential Tabular Data RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-01T22:52:38.890214Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T22:52:38.890214Z digest=sha256:217eaf117f5522d94197e9e41d29bd48d04ef2521d9393f741096f85221abe98

Observation 1ac4b28c-5765-4b44-b8bf-4a3ef25ce567 · inbound

PluRel-to-RDB-PFN: Schema-Guided Synthetic Relational Pretraining cites this paper.

PluRel-to-RDB-PFN: Schema-Guided Synthetic Relational Pretraining RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-03T13:14:31.613157Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T13:14:31.613157Z digest=sha256:cb7e8c53629eb44399c29db89c54a5099144a3f9d1be970684e256b8471cd888