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Paper Citation Record · LEDGER

Ambient Diffusion: Learning Clean Distributions from Corrupted Data

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2305.19256.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2305.19256 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:53:25.293080Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-19T21:02:47.340298Z

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 1f7cfcd1-1389-4fd7-a548-6ebc72732232 · inbound

Bootstrapping Diffusion: Diffusion Model Training Leveraging Partial and Corrupted Data cites this paper.

Bootstrapping Diffusion: Diffusion Model Training Leveraging Partial and Corrupted Data Ambient Diffusion: Learning Clean Distributions from Corrupted Data

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-15T20:53:25.293080Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:53:25.293080Z digest=sha256:c84cd41a5c3ddb8e348cd6c7faa7eecef10e9a31a914122b60784395c1564347

Observation 7cb3445d-b6fb-4855-92cc-5a7ca49aaddc · inbound

Observation-Aligned Mask Priors for Learning Physical Dynamics from Authentic Occlusions cites this paper.

Observation-Aligned Mask Priors for Learning Physical Dynamics from Authentic Occlusions Ambient Diffusion: Learning Clean Distributions from Corrupted Data

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-19T21:02:47.342064Z

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.

source=pdf_text observed=2026-05-19T20:59:55.644530Z digest=sha256:25670db27688c38e9ba2330b01b7b01ead6d36e08697e027932329c5edb3f5ca