Paper Citation Record · LEDGER

Graph Generative Pre-trained Transformer

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2501.01073.

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

pith.paper-citation-record.v1
2501.01073 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:36:20.663823Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T04:33:39.707945Z

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 d6b6c42f-52d2-4653-88a4-9954926f7595 · inbound

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

Retrieval-Augmented Generation with Graphs (GraphRAG) Graph Generative Pre-trained Transformer

Reference 52

Resolution: verified exact; arxiv_id, observed 2026-05-18T04:33:39.710198Z

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.

Observation 872c7629-18d2-41f9-a0b2-08e5cd8a4d13 · inbound

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation cites this paper.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation Graph Generative Pre-trained Transformer

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T16:36:20.663823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3f37a9e1-242d-4686-88ea-e879bcb27e1a · inbound

PROVCREATOR: Synthesizing Complex Heterogenous Graphs with Node and Edge Attributes cites this paper.

PROVCREATOR: Synthesizing Complex Heterogenous Graphs with Node and Edge Attributes Graph Generative Pre-trained Transformer

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T13:08:45.370911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aad9949d-f8a7-4d1b-9944-8563c10a8c7c · inbound

From GPT-3 to GPT-5: Mapping their capabilities, scope, limitations, and consequences cites this paper.

From GPT-3 to GPT-5: Mapping their capabilities, scope, limitations, and consequences Graph Generative Pre-trained Transformer

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-11T10:56:04.601347Z

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.