Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
AsCAN: Asymmetric Convolution-Attention Networks for Efficient Recognition and Generation
As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2411.04967.
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 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T16:56:01.653783Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-11T16:56:02.287972Z
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 30105d95-d86e-43fb-91bd-b9afaa3c23d4 · inbound
SnapGen: Taming High-Resolution Text-to-Image Models for Mobile Devices with Efficient Architectures and Training cites this paper.
SnapGen: Taming High-Resolution Text-to-Image Models for Mobile Devices with Efficient Architectures and Training AsCAN: Asymmetric Convolution-Attention Networks for Efficient Recognition and Generation
Reference 32
- Resolution
- verified exact
- local_arxiv, observed 2026-08-11T16:56:02.294501Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation c0c87f4c-f57c-47c4-9a49-eecbdfd6e5f9 · inbound
SnapGen++: Unleashing Diffusion Transformers for Efficient High-Fidelity Image Generation on Edge Devices cites this paper.
SnapGen++: Unleashing Diffusion Transformers for Efficient High-Fidelity Image Generation on Edge Devices AsCAN: Asymmetric Convolution-Attention Networks for Efficient Recognition and Generation
Reference 34
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T10:56:12.920321Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.