Paper Citation Record · LEDGER

Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2307.03393.

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

pith.paper-citation-record.v1
2307.03393 v4

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 2026-08-10T06:31:04.303077+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T13:08:45.492335Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T20:08:56.299248Z

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 d9b42afc-b77f-4451-993a-c92078bb0979 · inbound

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

PROVCREATOR: Synthesizing Complex Heterogenous Graphs with Node and Edge Attributes Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T13:08:45.492335Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d7e0fb5-9f70-4510-992b-cce1761cea61 · inbound

Where LLM Annotators Fail: Label-Free Learning on Graphs with LLMs cites this paper.

Where LLM Annotators Fail: Label-Free Learning on Graphs with LLMs Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-06-29T14:33:30.678721Z

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.

Observation 868b32a7-5353-4fe0-8201-437dd104635c · inbound

Probabilistic Salary Prediction with Graph Attention Networks and a Mixture Density Network cites this paper.

Probabilistic Salary Prediction with Graph Attention Networks and a Mixture Density Network Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-07-03T13:28:19.491725Z

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.

Observation 73f20bee-a6b5-4b84-b5f6-0b1796b7a8f6 · inbound

Handling Feature Heterogeneity with Learnable Graph Patches cites this paper.

Handling Feature Heterogeneity with Learnable Graph Patches Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-07-03T20:08:56.301589Z

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.