Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
XLSor: A Robust and Accurate Lung Segmentor on Chest X-Rays Using Criss-Cross Attention and Customized Radiorealistic Abnormalities Generation
As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1904.09229.
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 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-14T11:57:07.041419Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-14T10:46:04.101147Z
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 dddfff1f-309d-4e64-ba2c-aaf31366922d · inbound
TUNA-Net: Task-oriented UNsupervised Adversarial Network for Disease Recognition in Cross-Domain Chest X-rays cites this paper.
TUNA-Net: Task-oriented UNsupervised Adversarial Network for Disease Recognition in Cross-Domain Chest X-rays XLSor: A Robust and Accurate Lung Segmentor on Chest X-Rays Using Criss-Cross Attention and Customized Radiorealistic Abnormalities Generation
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T11:57:07.041419Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation aae397d2-282f-4d38-9e81-51e25914329d · inbound
Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation cites this paper.
Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation XLSor: A Robust and Accurate Lung Segmentor on Chest X-Rays Using Criss-Cross Attention and Customized Radiorealistic Abnormalities Generation
Reference 125
- Resolution
- verified exact
- local_arxiv, observed 2026-08-14T10:46:04.105082Z
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.