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Paper Citation Record · LEDGER

Autoregressive Models in Vision: A Survey

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 inbound Pith citation observations for arXiv:2411.05902.

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

pith.paper-citation-record.v1
2411.05902 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 15 of 15 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T13:54:33.859863Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T12:49:52.859276Z

Reference resolution

0 of 0 outbound references displayed

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  • verified fuzzy0
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  • malformed identifier0
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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 bce9d780-065b-4b7d-85bf-3a1fd0ee2013 · inbound

PanoLlama: Generating Endless and Coherent Panoramas with Next-Token-Prediction LLMs cites this paper.

PanoLlama: Generating Endless and Coherent Panoramas with Next-Token-Prediction LLMs Autoregressive Models in Vision: A Survey

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-12T13:54:33.859863Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:54:33.859863Z digest=sha256:b03c93c4a74efeb3ec71b51212f10a2ec22681dba2023885cf951aa695c68387

Observation 3b0035df-556a-42d0-a748-2c8e81ab871e · inbound

Identity-Preserving Text-to-Video Generation by Frequency Decomposition cites this paper.

Identity-Preserving Text-to-Video Generation by Frequency Decomposition Autoregressive Models in Vision: A Survey

Reference 75

Resolution
unresolved
no resolver link, observed 2026-08-12T12:10:27.372712Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T12:10:27.372712Z digest=sha256:41f6eb594a4af72a56bb744caef5172cac61f09d01bcf7df9a1f585559df6a45

Observation ffca2200-517f-416f-a903-5e3ab4cda93e · inbound

[MASK] is All You Need cites this paper.

[MASK] is All You Need Autoregressive Models in Vision: A Survey

Reference 80

Resolution
unresolved
no resolver link, observed 2026-08-11T19:29:21.205007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:29:21.205007Z digest=sha256:9c520d4571a390c140c1045a701652370490049e1a9e568f7618f8c78696ad23

Observation b9586c45-5905-4b34-b0da-3be87381ae11 · inbound

Multimodal Generative AI with Autoregressive LLMs for Human Motion Understanding and Generation: A Way Forward cites this paper.

Multimodal Generative AI with Autoregressive LLMs for Human Motion Understanding and Generation: A Way Forward Autoregressive Models in Vision: A Survey

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-07T12:06:23.551098Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:06:23.551098Z digest=sha256:40b6c2e5e2f5a322867a6febbe91bd29d257b6b55c8fb1dcf17093fc45a5818b

Observation 78fdd273-787d-4a46-bdf7-d02c1498ef5f · inbound

BulletGen: Improving 4D Reconstruction with Bullet-Time Generation cites this paper.

BulletGen: Improving 4D Reconstruction with Bullet-Time Generation Autoregressive Models in Vision: A Survey

Reference 80

Resolution
verified exact
arxiv_id, observed 2026-05-19T08:03:01.094244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T08:02:14.123151Z digest=sha256:82d2ebd420575f48e843090d62c2ce7002f152d6a03945f2b7de86f2c3d9d365

Observation 5b25831e-5295-43d6-83c5-bfc7c54cf5a3 · inbound

A Survey on Vision-Language-Action Models for Autonomous Driving cites this paper.

A Survey on Vision-Language-Action Models for Autonomous Driving Autoregressive Models in Vision: A Survey

Reference 137

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unresolved
no resolver link, observed 2026-08-06T21:31:04.806091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:31:04.806091Z digest=sha256:de02997b971c6f501ac2b87372a4ce64f5fa4de6ab74a3fe9fea9bad3333262d

Observation b0b0ce77-cd97-4ce9-b230-1575e9c3cc68 · inbound

A Survey on Training-free Alignment of Large Language Models cites this paper.

A Survey on Training-free Alignment of Large Language Models Autoregressive Models in Vision: A Survey

Reference 92

Resolution
unresolved
no resolver link, observed 2026-08-05T21:18:49.044177Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T21:18:49.044177Z digest=sha256:d0ba4c330b9d50af3979418cb5e46bc0b80d6c2ae534f3082fb2a65239ad92e1

Observation e5ef6492-9158-4167-bb9e-38560576de78 · inbound

A Unified Low-level Foundation Model for Enhancing Pathology Image Quality cites this paper.

A Unified Low-level Foundation Model for Enhancing Pathology Image Quality Autoregressive Models in Vision: A Survey

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-05T13:00:48.189650Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:00:48.189650Z digest=sha256:4230a67759b25493755ee8b3b33e602683cd708d666c39fc4754060b4ff457f1

Observation b63d9169-def5-4af6-ab4a-891d9b6a018c · inbound

Generative AI Meets 6G and Beyond: Diffusion Models for Semantic Communications cites this paper.

Generative AI Meets 6G and Beyond: Diffusion Models for Semantic Communications Autoregressive Models in Vision: A Survey

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-05-17T23:40:31.101868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-17T23:40:01.988138Z digest=sha256:f838e107920aeebd8fcbed19ea001d3f0313f7e1d277f3db2c16571ef43f8f66

Observation 32756b07-7c5a-4a08-8075-2cd47f5efb29 · inbound

Persistent Visual Memory: Sustaining Perception for Deep Generation in LVLMs cites this paper.

Persistent Visual Memory: Sustaining Perception for Deep Generation in LVLMs Autoregressive Models in Vision: A Survey

Reference 85

Resolution
verified exact
arxiv_id, observed 2026-05-11T16:01:22.428411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-09T18:53:06.494640Z digest=sha256:f1a160cfd25a6e7b5fa279c400131451d319ba2e7933507570d9840bead7c309

Observation feacafef-7fb4-4d97-94b4-479f6d129e74 · inbound

Persistent Visual Memory: Sustaining Perception for Deep Generation in LVLMs cites this paper.

Persistent Visual Memory: Sustaining Perception for Deep Generation in LVLMs Autoregressive Models in Vision: A Survey

Reference 85

Resolution
verified exact
arxiv_id, observed 2026-05-11T01:50:51.575223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-11T01:49:15.136031Z digest=sha256:e0109201a44acf16837a0e094a50b1390ce7fed5114b3a375951097df1c5b666

Observation a077f488-522c-4d11-a33e-fa4372dce36e · inbound

PathAR: Structure-First Autoregressive Synthesis of Multimodal Pathology Images cites this paper.

PathAR: Structure-First Autoregressive Synthesis of Multimodal Pathology Images Autoregressive Models in Vision: A Survey

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-07-01T22:06:15.894857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-28T15:50:54.950899Z digest=sha256:037b7ab00ed78fe02737f55b4edca98d0c77c2059ede539234739be94d8e3996

Observation 23c1441d-9ebf-42aa-9d12-905d76aafc44 · inbound

NEXUS: Neural Energy Fields for Physically Consistent Contact-Rich 3D Object Dynamics cites this paper.

NEXUS: Neural Energy Fields for Physically Consistent Contact-Rich 3D Object Dynamics Autoregressive Models in Vision: A Survey

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-07-03T17:18:43.309763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-27T04:25:27.067362Z digest=sha256:e07bf6584be8f43f0cfd51dd360cd4866ed011fad1f03ff58fb36537fac908e7

Observation 4e4dd0b6-d32f-4088-9f05-e56e3726c784 · inbound

Safe Autoregressive Image Generation with Iterative Self-Improving Codebooks cites this paper.

Safe Autoregressive Image Generation with Iterative Self-Improving Codebooks Autoregressive Models in Vision: A Survey

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-07-04T12:49:52.860606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-26T05:51:01.446139Z digest=sha256:e412f79ab5b200742743c57004d9c4e0399b2137967c2fd95e44fc439dde220a

Observation 76e2d6b2-bba3-4df6-8425-cba8a7dc73e6 · inbound

Does More Retrieved Evidence Help Visual Retrieval-Augmented Generation with Diffusion Language Models? cites this paper.

Does More Retrieved Evidence Help Visual Retrieval-Augmented Generation with Diffusion Language Models? Autoregressive Models in Vision: A Survey

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-10T16:51:18.564403Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:51:18.564403Z digest=sha256:4f86a958cfc0347a218c74d95be85cd1491e0a5447ebe27edb2b55cee1892c8f