Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Candidate Pseudolabel Learning: Enhancing Vision-Language Models by Prompt Tuning with Unlabeled Data
As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2406.10502.
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 2026-08-05T06:32:48.257954+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-02T16:42:42.870073Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-10T23:50:53.755219Z
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 ec955c4c-f3f0-4eaa-8765-52245f28e534 · inbound
Holistic Optimal Label Selection for Robust Prompt Learning under Partial Labels cites this paper.
Holistic Optimal Label Selection for Robust Prompt Learning under Partial Labels Candidate Pseudolabel Learning: Enhancing Vision-Language Models by Prompt Tuning with Unlabeled Data
Reference 45
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T23:50:53.758166Z
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.
Observation ad59e40e-ef10-48db-b470-dbd4729eb0a3 · inbound
Holistic Optimal Label Selection for Robust Prompt Learning under Partial Labels cites this paper.
Holistic Optimal Label Selection for Robust Prompt Learning under Partial Labels Candidate Pseudolabel Learning: Enhancing Vision-Language Models by Prompt Tuning with Unlabeled Data
Reference 45
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T16:42:42.870073Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.