Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
How Do Large Language Models Understand Graph Patterns? A Benchmark for Graph Pattern Comprehension
As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2410.05298.
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 2026-08-04T06:34:03.388597+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-28T22:39:04.557903Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
1
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation b5ba4689-c0cb-4224-a00f-d2c1c516361f · inbound
A Survey of Context Engineering for Large Language Models cites this paper.
A Survey of Context Engineering for Large Language Models How Do Large Language Models Understand Graph Patterns? A Benchmark for Graph Pattern Comprehension
Reference 201
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T20:58:45.197304Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 33f0f1de-5ddc-4cd8-aeae-bd72c27a5972 · inbound
GraphScout: Empowering Large Language Models with Intrinsic Exploration Ability for Agentic Graph Reasoning cites this paper.
GraphScout: Empowering Large Language Models with Intrinsic Exploration Ability for Agentic Graph Reasoning How Do Large Language Models Understand Graph Patterns? A Benchmark for Graph Pattern Comprehension
Reference 8
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T18:50:17.023174Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 9acffdbd-93aa-4140-bab3-b12fedb83350 · inbound
Evaluating LLMs on Large-Scale Graph Property Estimation via Random Walks cites this paper.
Evaluating LLMs on Large-Scale Graph Property Estimation via Random Walks How Do Large Language Models Understand Graph Patterns? A Benchmark for Graph Pattern Comprehension
Reference 40
- Resolution
- verified exact
- arxiv_id, observed 2026-05-09T22:13:57.926402Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d12a6472-fdc1-4758-8c2f-4a51dfdc9a0f · inbound
Revisiting Graph-Tokenizing Large Language Models: A Systematic Evaluation of Graph Token Understanding cites this paper.
Revisiting Graph-Tokenizing Large Language Models: A Systematic Evaluation of Graph Token Understanding How Do Large Language Models Understand Graph Patterns? A Benchmark for Graph Pattern Comprehension
Reference 1
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-12T11:01:31.328885Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 67c80638-da49-4224-93c9-8107f3a47747 · inbound
GraphARC: A Comprehensive Benchmark for Graph-Based Abstract Reasoning cites this paper.
GraphARC: A Comprehensive Benchmark for Graph-Based Abstract Reasoning How Do Large Language Models Understand Graph Patterns? A Benchmark for Graph Pattern Comprehension
Reference 6
- Resolution
- verified exact
- arxiv_id, observed 2026-06-28T22:42:46.620733Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.