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Paper Citation Record · LEDGER

GFS: Graph-based Feature Synthesis for Prediction over Relational Databases

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2312.02037.

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

pith.paper-citation-record.v1
2312.02037 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:31:43.605507Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T01:59:38.573013Z

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 6267dc01-95a1-46ec-88a3-550873055954 · 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 GFS: Graph-based Feature Synthesis for Prediction over Relational Databases

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-07T11:31:43.605507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:31:43.605507Z digest=sha256:35f06e89c08f8eff6c9df24831b4510dc865b4790e3bdf790f6cfa902fb2b466

Observation f6f6832a-0193-4c52-9574-9c70d829568d · inbound

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

No Need to Train Your RDB Foundation Model GFS: Graph-based Feature Synthesis for Prediction over Relational Databases

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-02T23:33:32.925139Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T23:33:32.925139Z digest=sha256:ad8c8aa82647052a604cd6cd6ee94c4ff1288b541691bd2e4b028ccd88adeb4b

Observation f3bd7019-1cad-436e-a7e9-2c3517851d0e · inbound

From Schema to Signal: Retrieval-Augmented Modeling for Relational Data Analytics cites this paper.

From Schema to Signal: Retrieval-Augmented Modeling for Relational Data Analytics GFS: Graph-based Feature Synthesis for Prediction over Relational Databases

Reference 46

Resolution
verified exact
arxiv_id, observed 2026-05-15T01:59:38.576050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-15T01:59:36.391925Z digest=sha256:649b787e65414a6fe2e3066ca3a92518d9bef2b6a98613df48bbe626d22cae9c

Observation ec0430f9-b750-4d60-8556-2338f2f56299 · inbound

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

Parameter-Free Encoders Remain Viable for RDB Foundation Models GFS: Graph-based Feature Synthesis for Prediction over Relational Databases

Reference 22

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=sha256:4cb5a380b8429bfd2ccc77d51a0b6f8ddb3b5215ab541609357b064fa6060e37

Observation 50dd5625-6b1f-4858-aad4-934cf73a40db · inbound

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

Parameter-Free Encoders Remain Viable for RDB Foundation Models GFS: Graph-based Feature Synthesis for Prediction over Relational Databases

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-02T08:36:04.690347Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T08:36:04.690347Z digest=sha256:bac748bef9543c5161356fbb5cf1801420f6e019b0b9efdf542653b9326dd8f7