Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Denoising: A Powerful Building-Block for Imaging, Inverse Problems, and Machine Learning
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2409.06219.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T13:15:04.354161Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, 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
3
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation cdc04a9e-9c08-4d3b-9b68-e68d6a5a4804 · inbound
A Survey on Diffusion Models for Inverse Problems cites this paper.
A Survey on Diffusion Models for Inverse Problems Denoising: A Powerful Building-Block for Imaging, Inverse Problems, and Machine Learning
Reference 111
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T04:31:49.262463Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 513d382d-cd14-4a35-aec4-1a6cab839a88 · inbound
Hypothesis Testing in Imaging Inverse Problems cites this paper.
Hypothesis Testing in Imaging Inverse Problems Denoising: A Powerful Building-Block for Imaging, Inverse Problems, and Machine Learning
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:15:04.354161Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f2197478-348b-432b-bba0-d421af9c4db1 · inbound
Unlearning with Asymmetric Sources: Improved Unlearning-Utility Trade-off with Public Data cites this paper.
Unlearning with Asymmetric Sources: Improved Unlearning-Utility Trade-off with Public Data Denoising: A Powerful Building-Block for Imaging, Inverse Problems, and Machine Learning
Reference 122
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T05:57:21.638231Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.