Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Simple and Robust Loss Design for Multi-Label Learning with Missing Labels
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2112.07368.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T19:40:49.559330Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T14:00:29.466334Z
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 e88d8879-2a00-4798-897c-382954f9a0e7 · inbound
Adaptation of Multi-modal Representation Models for Multi-task Surgical Computer Vision cites this paper.
Adaptation of Multi-modal Representation Models for Multi-task Surgical Computer Vision Simple and Robust Loss Design for Multi-Label Learning with Missing Labels
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:40:49.559330Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d5f5bb65-84f0-4a2e-a2dd-b0de5391555e · inbound
More Reliable Pseudo-labels, Better Performance: A Generalized Approach to Single Positive Multi-label Learning cites this paper.
More Reliable Pseudo-labels, Better Performance: A Generalized Approach to Single Positive Multi-label Learning Simple and Robust Loss Design for Multi-Label Learning with Missing Labels
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T15:11:46.346240Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4788ac9a-b604-41e0-8ec3-12a9d68e1207 · inbound
The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning cites this paper.
The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Simple and Robust Loss Design for Multi-Label Learning with Missing Labels
Reference 11
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T14:00:29.553750Z
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.