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Paper Citation Record · LEDGER

LinkGPT: Teaching Large Language Models To Predict Missing Links

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2406.04640.

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

pith.paper-citation-record.v1
2406.04640 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:51:12.759252Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T08:24:26.897653Z

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 712b8b6b-a003-4dc5-82bf-4fe534276ec4 · inbound

Retrieval-Augmented Generation with Graphs (GraphRAG) cites this paper.

Retrieval-Augmented Generation with Graphs (GraphRAG) LinkGPT: Teaching Large Language Models To Predict Missing Links

Reference 148

Resolution
verified exact
arxiv_id, observed 2026-05-18T04:33:39.701103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-18T04:33:39.076517Z digest=sha256:b3bde528e517c48b42982e2cbbb7ae1e50c69bd5a66266d5ba157e0bdc482cbf

Observation 70840c71-fbb6-40e0-a2c3-0b93d79e1d63 · inbound

Quantizing Text-attributed Graphs for Semantic-Structural Integration cites this paper.

Quantizing Text-attributed Graphs for Semantic-Structural Integration LinkGPT: Teaching Large Language Models To Predict Missing Links

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-06T15:51:12.759252Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:51:12.759252Z digest=sha256:cabf0be24cb99512dfa943906d43a83502974a0002a016daa6cd4e791b364481

Observation d4dfa5e8-e720-4692-bac7-847b5262a5d1 · inbound

Learning Chain Of Thoughts Prompts for Predicting Entities, Relations, and even Literals on Knowledge Graphs cites this paper.

Learning Chain Of Thoughts Prompts for Predicting Entities, Relations, and even Literals on Knowledge Graphs LinkGPT: Teaching Large Language Models To Predict Missing Links

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-05-11T10:11:15.088350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T15:35:06.449564Z digest=sha256:649632542c12b7da89fa5e8f285f93f2bc16419f69cf2dfb0bdfaa9c42866557

Observation a1219db8-9e69-4d0f-b5e8-8556c6a90eec · inbound

Protein Thoughts: Interpretable Reasoning with Tree of Thoughts and Embedding-Space Flow Matching for Protein-Protein Interaction Discovery cites this paper.

Protein Thoughts: Interpretable Reasoning with Tree of Thoughts and Embedding-Space Flow Matching for Protein-Protein Interaction Discovery LinkGPT: Teaching Large Language Models To Predict Missing Links

Reference 83

Resolution
verified exact
arxiv_id, observed 2026-05-22T02:10:55.991582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-22T02:10:15.644360Z digest=sha256:6fc91caea2a9d7dfd1c898741d66d9685e70bc4cb60d18878ffc5440130f6cd7

Observation 695d982d-4926-4c07-b2ed-67e0867a431f · inbound

PromptGNN-sim: Deep Fusion and Alignment of GNN and LLMs for Text-Attributed Graph Learning cites this paper.

PromptGNN-sim: Deep Fusion and Alignment of GNN and LLMs for Text-Attributed Graph Learning LinkGPT: Teaching Large Language Models To Predict Missing Links

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-06-30T08:24:26.899734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-30T06:06:46.108334Z digest=sha256:8fe6f1bb8ffa3fe36c1fe0e2d392122374b935ba3ff0486d28dcbcdc26bc48d8