Paper Citation Record · LEDGER

The CTU Prague Relational Learning Repository

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 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 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T18:10:37.021198Z

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 2026-08-13T06:32:02.005865+00:00.

Observation 9c0d6ba6-b553-4e3f-a7e9-909adcd8484e · inbound

Tackling prediction tasks in relational databases with LLMs cites this paper.

Tackling prediction tasks in relational databases with LLMs The CTU Prague Relational Learning Repository

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-12T18:10:37.021198Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 695868af-18d9-40b9-8252-5272dadafaa2 · inbound

Transformers Meet Relational Databases cites this paper.

Transformers Meet Relational Databases The CTU Prague Relational Learning Repository

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-11T20:54:08.926362Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fe3edd46-9586-416c-95c4-99a73c3706e1 · inbound

SALT: Sales Autocompletion Linked Business Tables Dataset cites this paper.

SALT: Sales Autocompletion Linked Business Tables Dataset The CTU Prague Relational Learning Repository

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-10T21:54:59.946900Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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 2026-08-13T06:32:02.005865+00:00.

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.

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.

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.

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.

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 2026-08-13T06:32:02.005865+00:00.

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.

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 2026-08-13T06:32:02.005865+00:00.

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.

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.