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Paper Citation Record · LEDGER

CNN-RNN: A Unified Framework for Multi-label Image Classification

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1604.04573.

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

pith.paper-citation-record.v1
1604.04573 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 2026-08-16T06:30:59.297886+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T12:24:29.655631Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-14T10:22:05.979341Z

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 7af2c9d7-188e-463f-bd90-fd284ed8e523 · inbound

Learning Semantic-Specific Graph Representation for Multi-Label Image Recognition cites this paper.

Learning Semantic-Specific Graph Representation for Multi-Label Image Recognition CNN-RNN: A Unified Framework for Multi-label Image Classification

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-14T12:24:29.655631Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T12:24:29.655631Z digest=sha256:faace5c72398b3efa7349a46b964820e0b9f79f0151585f1c04d6ae9dd86b18b

Observation 402b6e49-892f-487e-b671-cdb2a18763ae · inbound

Exploiting Temporality for Semi-Supervised Video Segmentation cites this paper.

Exploiting Temporality for Semi-Supervised Video Segmentation CNN-RNN: A Unified Framework for Multi-label Image Classification

Reference 26

Resolution
verified exact
local_arxiv, observed 2026-08-14T10:22:05.986511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T10:22:05.900756Z digest=sha256:19c84ff850d11edcb3a3bb5b8f190f4755aa9b989ee582a76b17de9f5f65b437