Paper Citation Record · LEDGER

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds

As of 7 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2608.04827.

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

pith.paper-citation-record.v1
2608.04827 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:39:00.993973Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

43 of 43 outbound references displayed

verified exact2
verified fuzzy33
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1bd5181e-9e62-4849-ab06-53f0c63101a9 · outbound

This paper cites Denoising diffusion probabilistic models,.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds Denoising diffusion probabilistic models,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T15:38:57.687786Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab199a13-b701-4dd5-9d6f-1443d5f2ca9a · outbound

This paper cites Generative modeling by esti- mating gradients of the data distribution,.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds Generative modeling by esti- mating gradients of the data distribution,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:07.749214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 50259c97-d89a-4747-a164-5cd36b5abd06 · outbound

This paper cites Elucidating the design space of diffusion-based generative models,.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds Elucidating the design space of diffusion-based generative models,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:07.597808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9ae72b3e-ba16-4036-b2fc-ac65058a0bb3 · outbound

This paper cites Text-to-video generation,.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds Text-to-video generation,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:07.427471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1b2d9a7e-5802-4dcf-a132-1fd9b83ccdd0 · outbound

This paper cites A connection between score matching and denoising autoencoders,.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds A connection between score matching and denoising autoencoders,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:07.265784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b8a79a54-1d32-4d00-8774-aee6fd277951 · outbound

This paper cites Deep unsupervised learning using nonequi- librium thermodynamics,.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds Deep unsupervised learning using nonequi- librium thermodynamics,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:07.078813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 29f87a21-080b-4c64-a2d0-e2d55b40ea82 · outbound

This paper cites Score-Based Generative Modeling through Stochastic Differential Equations.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds Score-Based Generative Modeling through Stochastic Differential Equations

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T15:38:58.063320Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f03795db-ae75-4755-b6cd-6ca13545857d · outbound

This paper cites Test- ing the manifold hypothesis,.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds Test- ing the manifold hypothesis,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:06.823713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5155e34e-4868-4072-9145-f0b3fd56f100 · outbound

This paper cites Extrinsic gaussian processes for regression and classification on manifolds,.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds Extrinsic gaussian processes for regression and classification on manifolds,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:06.623467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 904c7fa3-2637-468b-8cae-5ff89a3b146f · outbound

This paper cites Riemannian diffusion models,.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds Riemannian diffusion models,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:06.454178Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d36823ab-f1af-495d-add2-709b7268bbd8 · outbound

This paper cites Riemannian diffusion models,.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds Riemannian diffusion models,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:06.283096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 34f2311b-9a7e-4404-b3ca-dd09cd051d80 · outbound

This paper cites Generative modeling on manifolds through mixture of riemannian diffusion processes,.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds Generative modeling on manifolds through mixture of riemannian diffusion processes,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:06.097105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8c98af25-4e20-44ae-bbb2-3335eb7b7c40 · outbound

This paper cites High-resolution image synthesis with latent diffusion models,.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds High-resolution image synthesis with latent diffusion models,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T15:38:58.568511Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2dfdf889-b522-4d15-907e-0223f5a594cb · outbound

This paper cites An introduction to variational autoencoders,.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds An introduction to variational autoencoders,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:05.893253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation cb9c026b-bc17-467b-8e93-f32fc62ecace · outbound

This paper cites Probabilistic non-linear principal com- ponent analysis with gaussian process latent variable models,.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds Probabilistic non-linear principal com- ponent analysis with gaussian process latent variable models,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:05.680117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ef02b1fe-2784-41a4-8619-db40acde7c90 · outbound

This paper cites Learning for larger datasets with the gaussian process latent variable model,.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds Learning for larger datasets with the gaussian process latent variable model,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:05.504803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 09d798b2-0588-423f-98bc-48f41798558c · outbound

This paper cites Revis- 10 iting active sets for gaussian process decoders,.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds Revis- 10 iting active sets for gaussian process decoders,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:05.350482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6d7adf95-0dfc-4e23-b362-511be8252cc7 · outbound

This paper cites Columbia object image library (coil-100),.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds Columbia object image library (coil-100),

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:05.201889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation fe758a58-7b8b-4260-8d7a-a50bb917308d · outbound

This paper cites Deep learning techniques for automatic mri cardiac multi-structures segmentation and diagnosis: is the problem solved?.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds Deep learning techniques for automatic mri cardiac multi-structures segmentation and diagnosis: is the problem solved?

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:05.043421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation da93ce96-0968-49e7-bb59-d79cb07f3f39 · outbound

This paper cites Multi- centre, multi-vendor and multi-disease cardiac image segmentation challenge,.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds Multi- centre, multi-vendor and multi-disease cardiac image segmentation challenge,

Reference 20

Resolution: verified exact; raw_fallback, observed 2026-08-06T15:39:01.463267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7fb94d4e-669f-4e8f-b7d2-2391b7206900 · outbound

This paper cites Gradient-based learning applied to document recogni- tion,.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds Gradient-based learning applied to document recogni- tion,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:04.862659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2f6e787a-5748-4a20-8375-a3da2b5ce209 · outbound

This paper cites Metrics for Probabilistic Geometries.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds Metrics for Probabilistic Geometries

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-08-06T15:39:01.235383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d92a9ee4-172e-4d8c-9df3-929860fb4234 · outbound

This paper cites Fast and robust shortest paths on manifolds learned from data,.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds Fast and robust shortest paths on manifolds learned from data,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:04.620230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1b08a2ce-5f47-4ec1-81e1-ee5eb81b1849 · outbound

This paper cites Laplacian eigenmaps for dimensionality reduction and data representation,.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds Laplacian eigenmaps for dimensionality reduction and data representation,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:04.453713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7d67cc0d-2cdb-48f0-850e-b12ee824cb04 · outbound

This paper cites Nonlinear dimensionality reduction by locally linear embedding,.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds Nonlinear dimensionality reduction by locally linear embedding,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T15:38:59.435582Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 354cb097-4cba-47ef-a717-00d036036350 · outbound

This paper cites an unresolved cited work.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds Unresolved cited work

Reference 26

Resolution: unresolved; raw_fallback, observed 2026-08-06T15:39:04.285199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9ba6d135-3f8a-4178-bd1e-665b7b022f06 · outbound

This paper cites an unresolved cited work.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds Unresolved cited work

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T15:38:59.530307Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f5480e57-a9ef-4acf-8877-c61659797ee3 · outbound

This paper cites The non-central wishart distribution and certain problems of multivariate statistics,.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds The non-central wishart distribution and certain problems of multivariate statistics,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:04.133341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f87a4543-1770-4a53-a9c0-54d76722b70e · outbound

This paper cites Brownian motion and Riemannian geometry,.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds Brownian motion and Riemannian geometry,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:03.953057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7537c2d5-4572-4fa5-83f1-5bdaf387b6fd · outbound

This paper cites A brief introduction to Brownian motion on a Riemannian manifold,.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds A brief introduction to Brownian motion on a Riemannian manifold,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:03.848338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 29d279f0-ec53-464a-bd9b-ff4aeab76bda · outbound

This paper cites Higher-order implicit strong numerical schemes for stochastic differential equa- tions,.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds Higher-order implicit strong numerical schemes for stochastic differential equa- tions,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:03.738608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c3f230cd-1493-4dde-b08f-24f118864019 · outbound

This paper cites Lamberton and B.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds Lamberton and B

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:03.503711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5e5df275-5f5c-48b3-aeab-e33c4c8f3012 · outbound

This paper cites Estimation of non- normalized statistical models by score matching.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds Estimation of non- normalized statistical models by score matching

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:03.306976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 45207668-1e15-4ff2-a9c1-cdae169ac402 · outbound

This paper cites U- net: Convolutional networks for biomedical image segmentation,.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds U- net: Convolutional networks for biomedical image segmentation,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:03.096405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation bcbf893a-bbb9-4892-b2b4-4703a6bbbccf · outbound

This paper cites Riemann manifold langevin and hamiltonian monte carlo methods,.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds Riemann manifold langevin and hamiltonian monte carlo methods,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:02.755959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6304f0b6-10f4-4570-a128-e0b0a369f4de · outbound

This paper cites Stochastic gradient hamiltonian monte carlo,.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds Stochastic gradient hamiltonian monte carlo,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:02.487033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f9fb91cd-edaf-4580-9f43-314a81137868 · outbound

This paper cites Amari and H.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds Amari and H

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:02.195088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 424af5bd-59f1-4a50-8bee-550872567453 · outbound

This paper cites Classifier-Free Diffusion Guidance.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds Classifier-Free Diffusion Guidance

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-06T15:39:00.456600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a50fe172-f717-48a3-bd0f-bd645b0709ae · outbound

This paper cites Diffusion models beat gans on image synthesis,.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds Diffusion models beat gans on image synthesis,

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-06T15:39:00.671005Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation abb10f95-89db-41d7-808c-b2d3bd400f47 · outbound

This paper cites Progressive distillation for fast sampling of diffusion models,.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds Progressive distillation for fast sampling of diffusion models,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:02.056370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3ce11394-b2e8-472c-af38-3834f1ca2afa · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilibrium,.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds Gans trained by a two time-scale update rule converge to a local nash equilibrium,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:01.874384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e3527d28-26c5-4300-afaf-1f9503cc0079 · outbound

This paper cites The unreasonable effectiveness of deep fea- tures as a perceptual metric,.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds The unreasonable effectiveness of deep fea- tures as a perceptual metric,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:01.745551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f13e9be8-9d12-40f4-b59c-b2b319871384 · outbound

This paper cites The intrinsic dimension of images and its impact on learning,.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds The intrinsic dimension of images and its impact on learning,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:01.623697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

No inbound Pith citation observations are available.