Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Co-training with High-Confidence Pseudo Labels for Semi-supervised Medical Image Segmentation
As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2301.04465.
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 2026-08-13T06:32:02.005865+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T23:41:46.963824Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T20:28:55.438105Z
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 6e84f93a-b372-4ff7-84aa-286ed643f83d · inbound
Low-Contrast-Enhanced Contrastive Learning for Semi-Supervised Endoscopic Image Segmentation cites this paper.
Low-Contrast-Enhanced Contrastive Learning for Semi-Supervised Endoscopic Image Segmentation Co-training with High-Confidence Pseudo Labels for Semi-supervised Medical Image Segmentation
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T23:41:46.963824Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9aa517df-6a5b-4401-ba3f-07f96252747b · inbound
Learnable Prompting SAM-induced Knowledge Distillation for Semi-supervised Medical Image Segmentation cites this paper.
Learnable Prompting SAM-induced Knowledge Distillation for Semi-supervised Medical Image Segmentation Co-training with High-Confidence Pseudo Labels for Semi-supervised Medical Image Segmentation
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T12:54:14.199319Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 50a51ff0-f0c0-454a-b8cf-83577191e1f5 · inbound
Uncertainty-Guided Cross Attention Ensemble Mean Teacher for Semi-supervised Medical Image Segmentation cites this paper.
Uncertainty-Guided Cross Attention Ensemble Mean Teacher for Semi-supervised Medical Image Segmentation Co-training with High-Confidence Pseudo Labels for Semi-supervised Medical Image Segmentation
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T11:31:29.972183Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9d1c53ec-8dcd-4c79-b0da-a4beeb1e5bed · inbound
UniSemAlign: Text-Prototype Alignment with a Foundation Encoder for Semi-Supervised Histopathology Segmentation cites this paper.
UniSemAlign: Text-Prototype Alignment with a Foundation Encoder for Semi-Supervised Histopathology Segmentation Co-training with High-Confidence Pseudo Labels for Semi-supervised Medical Image Segmentation
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T07:20:57.908357Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 3b5e44e5-5183-4670-860b-92a43370a032 · inbound
Beyond Visual Cues: CoT-Enhanced Reasoning for Semi-supervised Medical Image Segmentation cites this paper.
Beyond Visual Cues: CoT-Enhanced Reasoning for Semi-supervised Medical Image Segmentation Co-training with High-Confidence Pseudo Labels for Semi-supervised Medical Image Segmentation
Reference 16
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-03T20:28:55.439387Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.