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Paper Citation Record · LEDGER

Modeling Multi-Hop Semantic Paths for Recommendation in Heterogeneous Information Networks

As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2505.05989.

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

pith.paper-citation-record.v1
2505.05989 v1

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 2026-08-05T06:32:48.257954+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T22:21:59.991084Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T18:32:37.198081Z

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 14c9103f-b148-4f72-a38b-26c518f643e8 · inbound

Multi-Level Service Performance Forecasting via Spatiotemporal Graph Neural Networks cites this paper.

Multi-Level Service Performance Forecasting via Spatiotemporal Graph Neural Networks Modeling Multi-Hop Semantic Paths for Recommendation in Heterogeneous Information Networks

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-05T22:21:59.991084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:21:59.991084Z digest=sha256:27ed7885c42768c57de6b08ad49ed4f4e6d351946ad60f18723b1a1b92c7e5e7

Observation e021e5f5-1d74-4cfb-b5e8-f3485a3387eb · inbound

Artificial Intelligence-Based Multiscale Temporal Modeling for Anomaly Detection in Cloud Services cites this paper.

Artificial Intelligence-Based Multiscale Temporal Modeling for Anomaly Detection in Cloud Services Modeling Multi-Hop Semantic Paths for Recommendation in Heterogeneous Information Networks

Reference 22

Resolution
verified exact
local_arxiv, observed 2026-08-05T18:32:37.278726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-08-05T18:32:32.593264Z digest=sha256:8a2aa3c4cbdc8cf69df41e386fd9205e083ad483f5fb53ccdb75d2b9650e3a8e