Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
GT2Vec: Large Language Models as Multi-Modal Encoders for Text and Graph-Structured Data
As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2410.11235.
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 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T13:09:39.774118Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-12T10:24:07.326298Z
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 b9270f94-5786-4eb8-8153-1b205a201de4 · inbound
Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval cites this paper.
Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval GT2Vec: Large Language Models as Multi-Modal Encoders for Text and Graph-Structured Data
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T13:09:39.774118Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d6aef712-9564-4205-a949-f92b788859cd · inbound
Enhancing Few-Shot Vision-Language Classification with Large Multimodal Model Features cites this paper.
Enhancing Few-Shot Vision-Language Classification with Large Multimodal Model Features GT2Vec: Large Language Models as Multi-Modal Encoders for Text and Graph-Structured Data
Reference 52
- Resolution
- verified exact
- local_arxiv, observed 2026-08-12T10:24:07.330290Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.