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Paper Citation Record · LEDGER

Unraveling the Smoothness Properties of Diffusion Models: A Gaussian Mixture Perspective

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2405.16418.

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

pith.paper-citation-record.v1
2405.16418 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T14:11:39.735563Z

measured 1 of 1 external citation measurements

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 1c2eb02f-42a9-473e-a2ea-927af4302547 · inbound

Numerical Pruning for Efficient Autoregressive Models cites this paper.

Numerical Pruning for Efficient Autoregressive Models Unraveling the Smoothness Properties of Diffusion Models: A Gaussian Mixture Perspective

Reference 103

Resolution
unresolved
no resolver link, observed 2026-08-11T14:11:27.177965Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:11:27.177965Z digest=sha256:8feb9632d4c00e310c6516e172004258b508813afdaa59dae0a7526e6ea7a98a

Observation 05941c42-febe-4fbf-92ed-1f05ae5a5117 · inbound

LazyDiT: Lazy Learning for the Acceleration of Diffusion Transformers cites this paper.

LazyDiT: Lazy Learning for the Acceleration of Diffusion Transformers Unraveling the Smoothness Properties of Diffusion Models: A Gaussian Mixture Perspective

Reference 92

Resolution
unresolved
no resolver link, observed 2026-08-11T14:11:39.735563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:11:39.735563Z digest=sha256:0b066c9819e33bbe632753c99eb0ef0f6f3be8ec5818d6e217939d5d664031b4

Observation f660f7e7-b0a1-4579-ba86-858c682b41af · inbound

High-Order Matching for One-Step Shortcut Diffusion Models cites this paper.

High-Order Matching for One-Step Shortcut Diffusion Models Unraveling the Smoothness Properties of Diffusion Models: A Gaussian Mixture Perspective

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-09T18:10:53.149284Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T18:10:53.149284Z digest=sha256:626bcba05471b2e700eb574174eb07a358842699a3ed20f0296b57475addf0d5

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.

source=pdf_text observed=2026-08-08T12:53:00.172338Z digest=sha256:a68db6e5907a47fa3cd2f7f4e4836251757ac6985efab2bc17e916a5f7c12cb3

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.

source=arxiv_source observed=2026-08-08T10:20:15.423342Z digest=sha256:d6c2a20e342cce2e37297aedf80864aec1c5811829343d79927357a39abbff37

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-10T18:15:58.587798Z digest=sha256:f94fc2804e5567688c451bdb4fe9b1c1bcdfa06837941d0ce44b2270180eb7a1