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Paper Citation Record · LEDGER

Relational Deep Learning: Graph Representation Learning on Relational Databases

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2312.04615.

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

pith.paper-citation-record.v1
2312.04615 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:37:11.662125Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T16:09:57.498942Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 7cf21dd9-2b58-4523-abae-62251cead23f · inbound

Retrieval-Augmented Generation with Graphs (GraphRAG) cites this paper.

Retrieval-Augmented Generation with Graphs (GraphRAG) Relational Deep Learning: Graph Representation Learning on Relational Databases

Reference 115

Resolution
verified exact
arxiv_id, observed 2026-05-18T04:33:39.356916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-18T04:33:39.076517Z digest=sha256:0af31a0831ca0f5305dd008d8e04dfecc8f25f2cb97624eee916e28b1fccdaeb

Observation b6bb5324-f093-4f6b-932d-773258d7afc5 · inbound

Joint Relational Database Generation via Graph-Conditional Diffusion Models cites this paper.

Joint Relational Database Generation via Graph-Conditional Diffusion Models Relational Deep Learning: Graph Representation Learning on Relational Databases

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-05-22T13:14:53.358746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-22T13:12:30.940265Z digest=sha256:ca7b5018fffd6321e0bd7566f18720d8233099395b961e805597eb27ad9f8cb3

Observation 66143597-0f3b-4c5d-b2a8-aa708f4801c3 · inbound

Graph World Model cites this paper.

Graph World Model Relational Deep Learning: Graph Representation Learning on Relational Databases

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-06T17:37:11.662125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:37:11.662125Z digest=sha256:99a0273cde71ced197fa0677dd75ff470f8a4d3b95d497e36853a5c2c55cbd60

Observation 46f5ec0e-1c66-43a2-8ab1-558a2f8a0987 · inbound

Graph-Based Feature Augmentation for Predictive Tasks on Relational Datasets cites this paper.

Graph-Based Feature Augmentation for Predictive Tasks on Relational Datasets Relational Deep Learning: Graph Representation Learning on Relational Databases

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-05T14:46:18.521561Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:46:18.521561Z digest=sha256:194d393f654957f775a8f155ca4f6db8fc558431b5fc229506fab9c4f62180d9

Observation 8bffa5ec-bdb0-4c7e-8d9f-8bf7e288fd7f · inbound

No Need to Train Your RDB Foundation Model cites this paper.

No Need to Train Your RDB Foundation Model Relational Deep Learning: Graph Representation Learning on Relational Databases

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-02T23:33:31.241867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T23:33:31.241867Z digest=sha256:22e0f0e84a4f8c187650e1fe8185333231a0de01a47d4a6c3f0a42378a27cad5

Observation ee7abc61-18cb-4368-9015-fa0d806f972e · inbound

RelPrism: A Multi-Faceted Pre-training Framework with Self-Generated Tasks for Relational Databases cites this paper.

RelPrism: A Multi-Faceted Pre-training Framework with Self-Generated Tasks for Relational Databases Relational Deep Learning: Graph Representation Learning on Relational Databases

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-25T05:05:22.319305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-25T05:05:04.461460Z digest=sha256:f2fb92a8160a3fd658585ef15ff077c2c32ee959aeeace0ef3a804b0fb59a4ec

Observation d145f58e-7a2f-40b8-9378-8766f161d923 · inbound

SemStruct: Contextualizing Semantic Embeddings with Structural Information for Schema Matching cites this paper.

SemStruct: Contextualizing Semantic Embeddings with Structural Information for Schema Matching Relational Deep Learning: Graph Representation Learning on Relational Databases

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-06-28T23:32:47.247739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-28T23:29:09.401657Z digest=sha256:fd0fdff9409805bae72aa40ea95e4abbe403085b255dc2c775fcd3206a6fdfe9

Observation ead0cdfa-a3a1-4bb3-bcd7-321c0fee9293 · inbound

The Post-GCN Decade Revisited: Curvature-Stratified Evaluation of Relational Learning cites this paper.

The Post-GCN Decade Revisited: Curvature-Stratified Evaluation of Relational Learning Relational Deep Learning: Graph Representation Learning on Relational Databases

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-07-02T11:56:55.654495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-28T02:40:03.713695Z digest=sha256:19ee90d34d8ced11a7039e7a74e5a6fdfee7ccf62d2974230e3c1dfc50c6bd34

Observation 8743008b-25ac-4a64-b6f8-5b9c3941938d · inbound

A Fair Evaluation of Graph Foundation Models for Node Property Prediction cites this paper.

A Fair Evaluation of Graph Foundation Models for Node Property Prediction Relational Deep Learning: Graph Representation Learning on Relational Databases

Reference 7

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T16:09:57.500389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-26T00:50:39.622302Z digest=sha256:30b3aa6ed2b42cb597cffec526a6092d08197fc43fc1f679d7aa81b199500a0c

Observation 8d778328-21e7-46c1-892b-245517396b65 · inbound

GNBAN: Graph Neural Basis Attention Networks for Long-Horizon Forecasting over Large Entity Sets cites this paper.

GNBAN: Graph Neural Basis Attention Networks for Long-Horizon Forecasting over Large Entity Sets Relational Deep Learning: Graph Representation Learning on Relational Databases

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-06-29T19:43:55.195708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-29T04:40:51.660790Z digest=sha256:4b7093b0bc1d605ee0b2e3e3f53df253de6ecd40822a6734917f0f2f38a3a42e

Observation fb304738-d620-41f8-bb06-122a3bb1414b · inbound

Parameter-Free Encoders Remain Viable for RDB Foundation Models cites this paper.

Parameter-Free Encoders Remain Viable for RDB Foundation Models Relational Deep Learning: Graph Representation Learning on Relational Databases

Reference 5

Resolution
unresolved
no resolver link, observed 2026-07-11T11:47:14.742492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T11:47:14.742492Z digest=sha256:12d39abdf422d5ef28e11d8743ed4b58961e96436ec76e78451c42268c3b7ed4

Observation 7904f7a3-de28-40bd-9dc2-8b00c5b5d6b9 · inbound

Parameter-Free Encoders Remain Viable for RDB Foundation Models cites this paper.

Parameter-Free Encoders Remain Viable for RDB Foundation Models Relational Deep Learning: Graph Representation Learning on Relational Databases

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-02T08:36:02.480788Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T08:36:02.480788Z digest=sha256:1b8fa6d5eeefd566160504292c355a8c7dfb29f79780f61c8b72e99d7a451b53

Observation aef72cfc-56b2-4bdd-b5c0-829e97c9aad2 · inbound

UniSAGE: Unifying Static and Dynamic Attributes with Hyper-Structure cites this paper.

UniSAGE: Unifying Static and Dynamic Attributes with Hyper-Structure Relational Deep Learning: Graph Representation Learning on Relational Databases

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-02T14:52:34.303291Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T14:52:34.303291Z digest=sha256:b0b73c9e7cfaf9fafc4c1f0d022cd28ec0b4d68e62679f78ce8c71d06acb233e