Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Denoising Score Distillation: From Noisy Diffusion Pretraining to One-Step High-Quality Generation
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2503.07578.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-03T08:02:20.623495Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T10:37:57.213882Z
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 cf4604d4-56e4-4fc1-95ec-d54a03a53636 · inbound
Generative Modeling from Black-box Corruptions via Self-Consistent Stochastic Interpolants cites this paper.
Generative Modeling from Black-box Corruptions via Self-Consistent Stochastic Interpolants Denoising Score Distillation: From Noisy Diffusion Pretraining to One-Step High-Quality Generation
Reference 8
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T23:03:39.123129Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 4dc7683a-e9d6-4d5a-941f-585004b7f05b · inbound
Riemannian AmbientFlow: Towards Simultaneous Manifold Learning and Generative Modeling from Corrupted Data cites this paper.
Riemannian AmbientFlow: Towards Simultaneous Manifold Learning and Generative Modeling from Corrupted Data Denoising Score Distillation: From Noisy Diffusion Pretraining to One-Step High-Quality Generation
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T08:02:20.623495Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ff1c019d-338f-4124-9aa5-0674005d1602 · inbound
Ambient Diffusion Policy: Imitation Learning from Suboptimal Data in Robotics cites this paper.
Ambient Diffusion Policy: Imitation Learning from Suboptimal Data in Robotics Denoising Score Distillation: From Noisy Diffusion Pretraining to One-Step High-Quality Generation
Reference 35
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T10:37:57.215601Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.