Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Are Large Language Models In-Context Graph Learners?
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2502.13562.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T11:09:42.254388Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-22T10:31:25.467593Z
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 ee87b732-f351-4de8-b859-1091d5fa76b0 · inbound
Are Large Language Models Good Temporal Graph Learners? cites this paper.
Are Large Language Models Good Temporal Graph Learners? Are Large Language Models In-Context Graph Learners?
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:09:42.254388Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8b625b7e-65f9-483e-99ee-20a716d9701b · inbound
Node-as-Agent: Graph Agentic Network cites this paper.
Node-as-Agent: Graph Agentic Network Are Large Language Models In-Context Graph Learners?
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T10:13:23.055816Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 59df3133-c469-445f-b1f7-a388d64ab850 · inbound
GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models cites this paper.
GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models Are Large Language Models In-Context Graph Learners?
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T23:37:56.167724Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f61103de-ea61-4720-8c4f-e7fdf5e075e9 · inbound
Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression cites this paper.
Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Are Large Language Models In-Context Graph Learners?
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T10:56:56.256191Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e092cfe2-dba1-4888-90f2-bc4b18307030 · inbound
Beyond One-Size-Fits-All: Adaptive Subgraph Denoising for Zero-Shot Graph Learning with Large Language Models cites this paper.
Beyond One-Size-Fits-All: Adaptive Subgraph Denoising for Zero-Shot Graph Learning with Large Language Models Are Large Language Models In-Context Graph Learners?
Reference 37
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T10:31:25.470334Z
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 313cb222-94e4-44ff-93a6-69780ddbba2b · inbound
Rethinking Efficient Graph Coarsening via a Non-Selfishness Principle cites this paper.
Rethinking Efficient Graph Coarsening via a Non-Selfishness Principle Are Large Language Models In-Context Graph Learners?
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-05-14T19:32:52.025339Z
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.