Paper Citation Record · LEDGER

Learning Mixtures of Gaussians Using the DDPM Objective

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2307.01178.

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

pith.paper-citation-record.v1
2307.01178 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T12:01:21.896651Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T05:39:40.852625Z

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 9f8128d3-f482-4eea-a7e1-71308d33c80c · inbound

A solvable generative model with a linear, one-step denoiser cites this paper.

A solvable generative model with a linear, one-step denoiser Learning Mixtures of Gaussians Using the DDPM Objective

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-12T12:01:21.896651Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 80fd25a0-2f09-4f6e-aec7-f3b7f20cf36c · inbound

A theory of learning data statistics in diffusion models, from easy to hard cites this paper.

A theory of learning data statistics in diffusion models, from easy to hard Learning Mixtures of Gaussians Using the DDPM Objective

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-05-21T11:34:08.940230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6ca74120-f4e5-467a-a5e3-3b3c71c3d985 · inbound

A theory of learning data statistics in diffusion models, from easy to hard cites this paper.

A theory of learning data statistics in diffusion models, from easy to hard Learning Mixtures of Gaussians Using the DDPM Objective

Reference 36

Resolution: unresolved; no resolver link, observed 2026-07-14T22:02:58.403878Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a61d6efe-f98a-4683-9654-e9bb6702a551 · inbound

Statistical Properties of Training & Generalization cites this paper.

Statistical Properties of Training & Generalization Learning Mixtures of Gaussians Using the DDPM Objective

Reference 265

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T05:39:40.854241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 823f5f6d-8173-493d-a75c-acb6fdd2429e · inbound

Statistical Properties of Training & Generalization cites this paper.

Statistical Properties of Training & Generalization Learning Mixtures of Gaussians Using the DDPM Objective

Reference 265

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T21:57:25.611609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.