Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Scaling Up Your Kernels to 31x31: Revisiting Large Kernel Design in CNNs
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2203.06717.
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 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T00:32:57.552039Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T02:28:24.338817Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
80
pith, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 9501e7b5-b298-44ae-9347-e26b2435db97 · inbound
Finding Optimal Kernel Size and Dimension in Convolutional Neural Networks An Architecture Optimization Approach cites this paper.
Finding Optimal Kernel Size and Dimension in Convolutional Neural Networks An Architecture Optimization Approach Scaling Up Your Kernels to 31x31: Revisiting Large Kernel Design in CNNs
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T00:32:57.552039Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7c69ffde-c6b7-4330-adbe-fbf6ec341694 · inbound
CARDIAG: A Dense Segment Classification Benchmark of Deep Learning Architectures for Coronary Angiography cites this paper.
CARDIAG: A Dense Segment Classification Benchmark of Deep Learning Architectures for Coronary Angiography Scaling Up Your Kernels to 31x31: Revisiting Large Kernel Design in CNNs
Reference 46
- Resolution
- verified exact
- local_arxiv, observed 2026-08-01T05:43:58.125340Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.