Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Unraveling the Smoothness Properties of Diffusion Models: A Gaussian Mixture Perspective
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2405.16418.
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 2026-08-08T12:53:00.172338Z
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
1
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 81f5e5ca-2bb3-4585-89e7-ff12e4f4b1a6 · inbound
Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms cites this paper.
Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms Unraveling the Smoothness Properties of Diffusion Models: A Gaussian Mixture Perspective
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T12:53:00.172338Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6cff407d-cd17-4948-bc9c-8e25735419e8 · inbound
Force Matching with Relativistic Constraints: A Physics-Inspired Approach to Stable and Efficient Generative Modeling cites this paper.
Force Matching with Relativistic Constraints: A Physics-Inspired Approach to Stable and Efficient Generative Modeling Unraveling the Smoothness Properties of Diffusion Models: A Gaussian Mixture Perspective
Reference 40
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T10:20:15.423342Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c7e20eeb-bdb0-45ff-b548-8b02cb658b8f · inbound
Lipschitz regularity in Flow Matching and Diffusion Models: sharp sampling rates and functional inequalities cites this paper.
Lipschitz regularity in Flow Matching and Diffusion Models: sharp sampling rates and functional inequalities Unraveling the Smoothness Properties of Diffusion Models: A Gaussian Mixture Perspective
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T20:30:47.464804Z
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.