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Paper Citation Record · LEDGER

Drug Similarity Integration Through Attentive Multi-view Graph Auto-Encoders

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1804.10850.

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

pith.paper-citation-record.v1
1804.10850 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 2026-08-22T06:32:14.747728+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:14:20.602075Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-16T11:14:20.954235Z

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 64c5f8fa-204b-4d4a-8029-ab471cf3cb06 · inbound

Disentangled Graph Representation Based on Substructure-Aware Graph Optimal Matching Kernel Convolutional Networks cites this paper.

Disentangled Graph Representation Based on Substructure-Aware Graph Optimal Matching Kernel Convolutional Networks Drug Similarity Integration Through Attentive Multi-view Graph Auto-Encoders

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-08-16T11:14:20.960931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T11:14:20.602075Z digest=sha256:ff030ca02a8120cc7af379f650c8d2b39796aed90841c247370f1e28b46e6398

Observation 36f6798b-13a2-439b-93bb-0e546a4197aa · inbound

CoFEND: A Cross-Modal Fusion End-to-End Network for Cold-Start Drug-Drug Interaction Prediction cites this paper.

CoFEND: A Cross-Modal Fusion End-to-End Network for Cold-Start Drug-Drug Interaction Prediction Drug Similarity Integration Through Attentive Multi-view Graph Auto-Encoders

Reference 53

Resolution
unresolved
no resolver link, observed 2026-07-12T06:03:24.750538Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T06:03:24.750538Z digest=sha256:13ccb1b4a9c7002bda8ec3b057c7b99e578f225e3dc2245533588ea35d0ed8f7