Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Segmentation and Recovery of Superquadric Models using Convolutional Neural Networks
As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2001.10504.
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 2026-08-22T06:32:14.747728+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T21:45:46.824363Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-19T21:42:48.133724Z
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 774641b3-2c8b-4cb7-86f1-f8e0bd35e270 · inbound
Supertoroid fitting of objects with holes for robotic grasping and scene generation cites this paper.
Supertoroid fitting of objects with holes for robotic grasping and scene generation Segmentation and Recovery of Superquadric Models using Convolutional Neural Networks
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:45:46.824363Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f587949d-2959-4f97-8891-edddeb895382 · inbound
A Holistic Method for Superquadric Fitting Using Unsupervised Clustering Analysis cites this paper.
A Holistic Method for Superquadric Fitting Using Unsupervised Clustering Analysis Segmentation and Recovery of Superquadric Models using Convolutional Neural Networks
Reference 20
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T21:42:48.135612Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.