Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Partitioned Hankel-based Diffusion Models for Few-shot Low-dose CT Reconstruction
As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2405.17167.
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 2026-08-13T06:32:02.005865+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-25T06:58:18.999912Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-25T07:00:27.022170Z
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 0d93037b-2b8c-4f1f-954c-65656c6d066e · inbound
Progressive $\mathcal{J}$-Invariant Self-supervised Learning for Low-Dose CT Denoising cites this paper.
Progressive $\mathcal{J}$-Invariant Self-supervised Learning for Low-Dose CT Denoising Partitioned Hankel-based Diffusion Models for Few-shot Low-dose CT Reconstruction
Reference 18
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T12:27:52.201137Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 8d94acf4-2fdc-4579-b27c-0e98dd6b4922 · inbound
Progressive $\mathcal{J}$-Invariant Self-supervised Learning for Low-Dose CT Denoising cites this paper.
Progressive $\mathcal{J}$-Invariant Self-supervised Learning for Low-Dose CT Denoising Partitioned Hankel-based Diffusion Models for Few-shot Low-dose CT Reconstruction
Reference 18
- Resolution
- verified exact
- arxiv_id, observed 2026-05-25T07:00:27.025421Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.