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Paper Citation Record · LEDGER

CV-VAE: A Compatible Video VAE for Latent Generative Video Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2405.20279.

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

pith.paper-citation-record.v1
2405.20279 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:14:21.136900Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T11:46:56.051112Z

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 a2164991-e91f-4346-9582-6048747f5b5c · inbound

SkyReels-V2: Infinite-length Film Generative Model cites this paper.

SkyReels-V2: Infinite-length Film Generative Model CV-VAE: A Compatible Video VAE for Latent Generative Video Models

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-05-14T20:23:04.190080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-14T20:23:04.022599Z digest=sha256:faba082527cdbf6e6e961f34edd0eff12708642d0470c4764d4a908e54adc69a

Observation 99ab9c85-0178-4c01-9f02-1f10d5ed141b · inbound

Interspatial Attention for Efficient 4D Human Video Generation cites this paper.

Interspatial Attention for Efficient 4D Human Video Generation CV-VAE: A Compatible Video VAE for Latent Generative Video Models

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T15:14:21.136900Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:14:21.136900Z digest=sha256:e6abd76e6c2827e3818316289b8bec2b9ccd427fe57ef360b19501c5807840b1

Observation 95783926-19f6-421e-a31b-5d585f60afa9 · inbound

Hi-VAE: Efficient Video Autoencoding with Global and Detailed Motion cites this paper.

Hi-VAE: Efficient Video Autoencoding with Global and Detailed Motion CV-VAE: A Compatible Video VAE for Latent Generative Video Models

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-07T05:47:18.345750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:47:18.345750Z digest=sha256:12b882098776862d7f05193bf3992f04f791da77d4395ed5ca6939687aa385e1

Observation a9e58314-9994-4bde-b334-7b66a04ba59a · inbound

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians cites this paper.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians CV-VAE: A Compatible Video VAE for Latent Generative Video Models

Reference 84

Resolution
unresolved
no resolver link, observed 2026-08-06T05:40:03.827247Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:40:03.827247Z digest=sha256:d963782c235af39898c9fdea2672fb74d052b6b44409ec535bb3351de8a01555

Observation b9c03e4f-0163-494d-b78f-6082d97ccb9d · inbound

HumanGenesis: Agent-Based Geometric and Generative Modeling for Synthetic Human Dynamics cites this paper.

HumanGenesis: Agent-Based Geometric and Generative Modeling for Synthetic Human Dynamics CV-VAE: A Compatible Video VAE for Latent Generative Video Models

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-05T20:49:53.744497Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T20:49:53.744497Z digest=sha256:c915820eb3a6cbe14dfe88e13c150a505796d4b157c97ba869d408042645555a

Observation d2d4cfe0-9b83-4b04-aeb0-14ae27742626 · inbound

Efficient Video Diffusion Models: Advancements and Challenges cites this paper.

Efficient Video Diffusion Models: Advancements and Challenges CV-VAE: A Compatible Video VAE for Latent Generative Video Models

Reference 192

Resolution
verified exact
arxiv_id, observed 2026-05-10T09:03:26.320237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T08:28:29.706249Z digest=sha256:1eec2d7013c844d08d23146cf8f303fa7a125537fb1806850ecd50806d9a007f

Observation 977ee4fa-8904-4d96-bd44-93cde8d0e77b · inbound

Adaptive Tokenisation Via Temporal Redundancy Masking And Latent Inpainting cites this paper.

Adaptive Tokenisation Via Temporal Redundancy Masking And Latent Inpainting CV-VAE: A Compatible Video VAE for Latent Generative Video Models

Reference 38

Resolution
verified exact
arxiv_id, observed 2026-07-02T11:46:56.052811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-28T02:55:00.586061Z digest=sha256:9bdc2c7ddabcdc05b47dcdab318473a8310b06c20dd463fc0344d5b7995d4b50