Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs
As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2307.03393.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-29T14:26:07.597446Z
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 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 2026-08-06T06:34:29.942622+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 2026-08-06T06:34:29.942622+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 2026-08-06T06:34:29.942622+00:00.