Paper Citation Record · LEDGER

Deep Generative Models through the Lens of the Manifold Hypothesis: A Survey and New Connections

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2404.02954.

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

pith.paper-citation-record.v1
2404.02954 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T14:06:22.481158Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T20:03:56.273033Z

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 530ad0a2-2b70-421c-8944-5dd81ddfb2eb · inbound

Anomaly Detection via Autoencoder Composite Features and NCE cites this paper.

Anomaly Detection via Autoencoder Composite Features and NCE Deep Generative Models through the Lens of the Manifold Hypothesis: A Survey and New Connections

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-09T14:06:22.481158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af827495-8bfb-48f2-9314-743ced20a950 · inbound

Variational Rank Reduction Autoencoders for Generative Thermal Design cites this paper.

Variational Rank Reduction Autoencoders for Generative Thermal Design Deep Generative Models through the Lens of the Manifold Hypothesis: A Survey and New Connections

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-04T20:35:23.477363Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7398303d-4f4b-4d6f-81c6-f1b96cc21a8e · inbound

Learning Latent Energy-Based Models via Interacting Particle Langevin Dynamics cites this paper.

Learning Latent Energy-Based Models via Interacting Particle Langevin Dynamics Deep Generative Models through the Lens of the Manifold Hypothesis: A Survey and New Connections

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:01.735841Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab26f6fe-c7de-4efb-99d4-f0f5a5571088 · inbound

Why Code, Why Now: An Information-Theoretic Perspective on the Limits of Machine Learning cites this paper.

Why Code, Why Now: An Information-Theoretic Perspective on the Limits of Machine Learning Deep Generative Models through the Lens of the Manifold Hypothesis: A Survey and New Connections

Reference 28

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T21:56:40.617030Z

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 74a49d7a-a5e4-48c0-a60f-f52444c1543f · inbound

Bi-Lipschitz Autoencoder With Injectivity Guarantee cites this paper.

Bi-Lipschitz Autoencoder With Injectivity Guarantee Deep Generative Models through the Lens of the Manifold Hypothesis: A Survey and New Connections

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T00:15:55.045437Z

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 242f04eb-6302-4759-8776-7a50607a7521 · inbound

What Matters for Diffusion-Friendly Latent Manifold? Prior-Aligned Autoencoders for Latent Diffusion cites this paper.

What Matters for Diffusion-Friendly Latent Manifold? Prior-Aligned Autoencoders for Latent Diffusion Deep Generative Models through the Lens of the Manifold Hypothesis: A Survey and New Connections

Reference 54

Resolution: verified exact; arxiv_id, observed 2026-05-11T04:05:57.588972Z

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 b5755060-f21c-4554-b27b-bb38217347ea · inbound

Provably Learning Diffusion Models under the Manifold Hypothesis: Collapse and Refine cites this paper.

Provably Learning Diffusion Models under the Manifold Hypothesis: Collapse and Refine Deep Generative Models through the Lens of the Manifold Hypothesis: A Survey and New Connections

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-05-21T07:39:49.358876Z

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 b2701598-7096-40ac-bf93-cf166a78cfa1 · inbound

Localizing Memorized Regions in Diffusion Models via Coordinate-Wise Curvature Differences cites this paper.

Localizing Memorized Regions in Diffusion Models via Coordinate-Wise Curvature Differences Deep Generative Models through the Lens of the Manifold Hypothesis: A Survey and New Connections

Reference 1

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T20:03:56.274419Z

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.