Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Polite Teacher: Semi-Supervised Instance Segmentation with Mutual Learning and Pseudo-Label Thresholding
As of 24 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2211.03850.
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 2026-08-23T06:30:58.430688+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-09T05:31:07.120236Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-08T14:29:00.953247Z
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 abb75222-46ad-41f8-ae98-8a631b508145 · inbound
A Unified Framework for Semi-Supervised Image Segmentation and Registration cites this paper.
A Unified Framework for Semi-Supervised Image Segmentation and Registration Polite Teacher: Semi-Supervised Instance Segmentation with Mutual Learning and Pseudo-Label Thresholding
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T05:31:07.120236Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3999f72d-37b6-4ef9-9484-2ce44dc310ef · inbound
SAMRefiner: Taming Segment Anything Model for Universal Mask Refinement cites this paper.
SAMRefiner: Taming Segment Anything Model for Universal Mask Refinement Polite Teacher: Semi-Supervised Instance Segmentation with Mutual Learning and Pseudo-Label Thresholding
Reference 14
- Resolution
- verified exact
- local_arxiv, observed 2026-08-08T14:29:00.960351Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.