Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Efficient Deformable ConvNets: Rethinking Dynamic and Sparse Operator for Vision Applications
As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2401.06197.
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 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T21:13:30.317295Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-10T23:19:25.809739Z
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 bc52709a-1eed-4aab-9680-d9dafcb5d1b4 · inbound
CoMiX: Cross-Modal Fusion with Deformable Convolutions for HSI-X Semantic Segmentation cites this paper.
CoMiX: Cross-Modal Fusion with Deformable Convolutions for HSI-X Semantic Segmentation Efficient Deformable ConvNets: Rethinking Dynamic and Sparse Operator for Vision Applications
Reference 54
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T21:13:30.317295Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c2e62a13-ea4e-4992-99b1-06a7afea8719 · inbound
Conformable Convolution for Topologically Aware Learning of Complex Anatomical Structures cites this paper.
Conformable Convolution for Topologically Aware Learning of Complex Anatomical Structures Efficient Deformable ConvNets: Rethinking Dynamic and Sparse Operator for Vision Applications
Reference 48
- Resolution
- verified exact
- local_arxiv, observed 2026-08-10T23:19:25.817367Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.