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Paper Citation Record · LEDGER

Large Language Models as Topological Structure Enhancers for Text-Attributed Graphs

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2311.14324.

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

pith.paper-citation-record.v1
2311.14324 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:44:53.289692Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T23:19:27.964642Z

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 da52ecd8-802e-44c1-8c78-46be6e213b6c · inbound

Efficient Text-Attributed Graph Learning through Selective Annotation and Graph Alignment cites this paper.

Efficient Text-Attributed Graph Learning through Selective Annotation and Graph Alignment Large Language Models as Topological Structure Enhancers for Text-Attributed Graphs

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-07T05:44:53.289692Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:44:53.289692Z digest=sha256:e1f570fa449bbc53fe9509f4f4d5954416242c9addbc7e1626dfca4efd1053fd

Observation cc89aba4-8199-42df-b73a-7ef8368eb850 · inbound

Robust Anomaly Detection in Network Traffic: Evaluating Machine Learning Models on CICIDS2017 cites this paper.

Robust Anomaly Detection in Network Traffic: Evaluating Machine Learning Models on CICIDS2017 Large Language Models as Topological Structure Enhancers for Text-Attributed Graphs

Reference 25

Resolution
verified exact
local_arxiv, observed 2026-08-06T23:19:28.030399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T23:19:27.724788Z digest=sha256:e61ca47325e7e54a711f5e7e1b62e2e21c173fa9866fbc4367ba3ffc37624dd1