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Paper Citation Record · LEDGER

The CTU Prague Relational Learning Repository

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:1511.03086.

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

pith.paper-citation-record.v1
1511.03086 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:05:07.741940Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T06:09:37.809889Z

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 13928cd1-3925-425b-b5f7-1772c6d84f0a · inbound

A Layered Aggregate Engine for Analytics Workloads cites this paper.

A Layered Aggregate Engine for Analytics Workloads The CTU Prague Relational Learning Repository

Reference 42

Resolution
verified exact
arxiv_id, observed 2026-05-25T18:56:09.171231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-25T18:51:26.166895Z digest=sha256:0143d521173ab75f7fd2b67a1db7759776fd7871201ce6c023725be841f2c831

Observation feb47191-f060-4af5-aa9c-1c8e2111d24e · inbound

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

Joint Relational Database Generation via Graph-Conditional Diffusion Models The CTU Prague Relational Learning Repository

Reference 38

Resolution
verified exact
arxiv_id, observed 2026-05-22T13:14:53.354462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-22T13:12:30.940265Z digest=sha256:aaaa3f4f71fc8418aa89c31425ec0fae051b4bea87f9b4624266db4f380d68e6

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

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models cites this paper.

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:aaf2ccb60b6dc7f7821c1c7b91c7c63f10066f2b7d06f025e1939e96794eb4bf

Observation 82a257dd-9933-4406-bfe5-7a95ce8a0e3a · inbound

From Features to Structure: Task-Aware Graph Construction for Relational and Tabular Learning with GNNs cites this paper.

From Features to Structure: Task-Aware Graph Construction for Relational and Tabular Learning with GNNs The CTU Prague Relational Learning Repository

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T11:31:43.118565Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:31:43.118565Z digest=sha256:25bd1ebfb257fa7dee8cd6b02bf94f146ebae8b312d18a3136bcb40a52519b12

Observation b6c3adc1-cd07-4638-aea4-a3a742021262 · inbound

Rel-HNN: Split Parallel Hypergraph Neural Network for Learning on Relational Databases cites this paper.

Rel-HNN: Split Parallel Hypergraph Neural Network for Learning on Relational Databases The CTU Prague Relational Learning Repository

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-06T16:49:10.981563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:49:10.981563Z digest=sha256:9155b2eb605501379a7a79ebb48806bf40843ffd30595b237322cee1b4a57f71

Observation d5cbbc5b-13d6-4132-9542-3e174d9ab221 · inbound

Synthesize, Retrieve, and Propagate: A Unified Predictive Modeling Framework for Relational Databases cites this paper.

Synthesize, Retrieve, and Propagate: A Unified Predictive Modeling Framework for Relational Databases The CTU Prague Relational Learning Repository

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-05T22:17:47.574456Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T22:17:47.574456Z digest=sha256:8b56dd8e0c192a5fef0ba854c32cd8c8ac4b9a800e466c6dd6d2aa9fd64081d4

Observation 6e1926bf-02b9-445e-a8f9-3e13bf2e3c24 · 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 The CTU Prague Relational Learning Repository

Reference 9

Resolution
metadata mismatch
arxiv_id, observed 2026-05-16T02:02:06.863931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-16T02:01:21.704891Z digest=sha256:0b211af228fadccf218896b00b0bb5055baf9b68bd09da6f1f256725acba4eda

Observation 2ebc4a0e-6963-4451-b7b9-d13b740932a1 · inbound

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

No Need to Train Your RDB Foundation Model The CTU Prague Relational Learning Repository

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-02T23:33:32.061746Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T23:33:32.061746Z digest=sha256:c8c6311039be9d8f2d1939f7fa6adb69524cb07fbe6f5bd62510df6bb130b0b8

Observation 42f668ef-3809-4396-9f4e-9e8f166c0f5e · inbound

Universal Encoders for Modular Relational Deep Learning cites this paper.

Universal Encoders for Modular Relational Deep Learning The CTU Prague Relational Learning Repository

Reference 19

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T06:09:37.811762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-26T14:44:38.182752Z digest=sha256:8370b156c59a1b8b546b32fb5d23fec940342e9bfa01df3bc15ea040deb3f4b2

Observation 48128bf9-00dd-41f0-8f04-892a7ff65240 · inbound

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

Parameter-Free Encoders Remain Viable for RDB Foundation Models The CTU Prague Relational Learning Repository

Reference 14

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:c9aadbc38230c5c10a3d654cae659a34ead6a979b549eb7e63d856524fdc1299

Observation 52569540-c1a8-41dc-991a-8d411e141d90 · inbound

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

Parameter-Free Encoders Remain Viable for RDB Foundation Models The CTU Prague Relational Learning Repository

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-02T08:36:03.665812Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T08:36:03.665812Z digest=sha256:2317a5c7ce0ff4880d0d8f9bcb1c38151af53298fccc9c3a585092c621c98e9d