ARCON: Advancing Auto-Regressive Continuation for Driving Videos | Paper Citation Record

Observation 5ca0bd72-10b2-4c9b-ad86-bd3be63cb624 · outbound

This paper cites 4m-21: An any-to-any vision model for tens of tasks and modalities.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos 4m-21: An any-to-any vision model for tens of tasks and modalities

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.297674Z

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Observation 9e947db1-1ad2-4d3d-b071-b06f79762e65 · outbound

This paper cites Sequential modeling enables scalable learn- ing for large vision models.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Sequential modeling enables scalable learn- ing for large vision models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.305995Z

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Observation 31befbeb-4b35-434b-b1d1-e235947529eb · outbound

This paper cites Video pretraining (vpt): Learning to act by watching unlabeled online videos.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Video pretraining (vpt): Learning to act by watching unlabeled online videos

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.312549Z

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Observation 1f506d08-5f11-4717-8f22-93b7a2495b5d · outbound

This paper cites Beit: Bert pre-training of image transformers.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Beit: Bert pre-training of image transformers

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.320069Z

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Observation 61762b9d-4ed9-4a66-8d49-9be50bab4b6c · outbound

This paper cites Video generation models as world simulators.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Video generation models as world simulators

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.328107Z

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Observation 4cf59159-3bff-4ab0-8344-a1957863856a · outbound

This paper cites Language models are few-shot learners.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Language models are few-shot learners

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.340294Z

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Observation 9a913dc4-cbaa-4a16-a7a5-7dff43bf0af2 · outbound

This paper cites nuscenes: A multi- modal dataset for autonomous driving.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos nuscenes: A multi- modal dataset for autonomous driving

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.349287Z

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Observation 010ab84f-bd40-4c1f-92c0-b7f188af3b6d · outbound

This paper cites Quo vadis, action recognition? a new model and the kinetics dataset.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Quo vadis, action recognition? a new model and the kinetics dataset

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.360824Z

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Observation 59435cbb-24e8-4fd4-801d-fc2112c07d8c · outbound

This paper cites A Short Note on the Kinetics-700 Human Action Dataset.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos A Short Note on the Kinetics-700 Human Action Dataset

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.374092Z

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Observation c9d73ed8-ea3a-4b3c-8899-bd749913039b · outbound

This paper cites Maskgit: Masked generative image transformer.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Maskgit: Masked generative image transformer

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.382383Z

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Observation 6d2dc819-01cb-4cbe-853b-d702564254de · outbound

This paper cites Generative pre- training from pixels.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Generative pre- training from pixels

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.387557Z

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Observation 91d892b5-28e9-4cb3-90f4-3172399cde5b · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos An image is worth 16x16 words: Transformers for image recognition at scale

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.405864Z

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Observation 3bdfc64c-4c0d-4bc2-87b8-1fcfc78fffae · outbound

This paper cites Taming transformers for high-resolution image synthesis.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Taming transformers for high-resolution image synthesis

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.414114Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c3a5c70-61d2-494e-aa1f-6ab3d30426b7 · outbound

This paper cites Taming transformers for high-resolution image synthesis.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Taming transformers for high-resolution image synthesis

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.423018Z

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Observation 59a65472-ec2b-4512-a023-4b9d749e5a87 · outbound

This paper cites Restructuring Vector Quantization with the Rotation Trick.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Restructuring Vector Quantization with the Rotation Trick

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.437454Z

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Observation 220940eb-0a4b-41a9-bbc9-6effe629c0b6 · outbound

This paper cites Vista: A Generalizable Driving World Model with High Fidelity and Versatile Controllability.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Vista: A Generalizable Driving World Model with High Fidelity and Versatile Controllability

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.444677Z

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Observation 71366443-ffff-443e-8ee4-2f80e2d9142b · outbound

This paper cites Simvp: Simpler yet better video prediction.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Simvp: Simpler yet better video prediction

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:11:54.937035Z

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Observation dfd16095-f421-49c8-b3a9-94e8fe1f87fe · outbound

This paper cites Worldgpt: Empowering llm as multimodal world model.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Worldgpt: Empowering llm as multimodal world model

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:11:54.918504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e445c23d-9858-4d3d-988d-a8b201528cdb · outbound

This paper cites Imagebind: One embedding space to bind them all.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Imagebind: One embedding space to bind them all

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:11:54.894646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b124ba76-0c48-474f-b54b-9c607d9288c6 · outbound

This paper cites Photorealistic Video Generation with Diffusion Models.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Photorealistic Video Generation with Diffusion Models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.484101Z

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Observation 0efcf9cd-b4bc-4348-9ca6-fd4bed4ff06b · outbound

This paper cites Recurrent world models facilitate policy evolution.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Recurrent world models facilitate policy evolution

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:11:54.872614Z

Source-reported events for the cited work

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Observation db28c11b-4964-4825-8e3d-3dac0c8b56ab · outbound

This paper cites Mastering Diverse Domains through World Models.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Mastering Diverse Domains through World Models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.502368Z

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Observation 56f010cf-b3cf-4a15-8230-8b9d28715e49 · outbound

This paper cites Masked autoencoders are scalable vision learners.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Masked autoencoders are scalable vision learners

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.510644Z

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Observation 9fe52c10-76d8-4a16-9143-c8f081afe4cb · outbound

This paper cites StreamingT2V: Consistent, Dynamic, and Extendable Long Video Generation from Text.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos StreamingT2V: Consistent, Dynamic, and Extendable Long Video Generation from Text

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.518291Z

Source-reported events for the cited work

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Observation 2169e6cf-dfc4-4a12-a849-2f05c3835ce7 · outbound

This paper cites GAIA-1: A Generative World Model for Autonomous Driving.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos GAIA-1: A Generative World Model for Autonomous Driving

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.524233Z

Source-reported events for the cited work

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Observation 3a5c4acf-af3a-46f0-b3f7-b16466cf5001 · outbound

This paper cites A dynamic multi-scale voxel flow network for video prediction.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos A dynamic multi-scale voxel flow network for video prediction

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:11:54.839343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9acad089-1f21-497d-9a75-b60439efa4ba · outbound

This paper cites DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.549073Z

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Observation bc66bf69-6e96-4243-8ffc-252775dee326 · outbound

This paper cites Step-Audio: Unified Understanding and Generation in Intelligent Speech Interaction.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Step-Audio: Unified Understanding and Generation in Intelligent Speech Interaction

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.558137Z

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Observation b6e9f28e-5bca-4e47-8bfa-838266e33b5d · outbound

This paper cites SubjectDrive: Scaling Generative Data in Autonomous Driving via Subject Control.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos SubjectDrive: Scaling Generative Data in Autonomous Driving via Subject Control

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.567200Z

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Observation 61d637d6-27b8-4ea2-9a24-08228bf1b978 · outbound

This paper cites Bert: Pre-training of deep bidirectional trans- formers for language understanding.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Bert: Pre-training of deep bidirectional trans- formers for language understanding

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:11:54.814780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8c0d0e86-7dfa-417d-b201-c0071c70df32 · outbound

This paper cites Drivegan: Towards a controllable high-quality neural simulation.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Drivegan: Towards a controllable high-quality neural simulation

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.595832Z

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Observation a013a7e9-65ce-4223-b9ac-3592cbda47c0 · outbound

This paper cites VideoPoet: A Large Language Model for Zero-Shot Video Generation.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos VideoPoet: A Large Language Model for Zero-Shot Video Generation

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.605598Z

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Observation 166e6dcc-650b-4a0c-b2eb-ff66d72b9ddf · outbound

This paper cites Uniformer: Uni- fying convolution and self-attention for visual recognition.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Uniformer: Uni- fying convolution and self-attention for visual recognition

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:11:54.783133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a0fc5fd5-fcb8-4acf-a030-ba2158849880 · outbound

This paper cites DrivingDiffusion: Layout-Guided multi-view driving scene video generation with latent diffusion model.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos DrivingDiffusion: Layout-Guided multi-view driving scene video generation with latent diffusion model

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.623864Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f6e91049-1e55-4efd-b715-1b5b4d001bf4 · outbound

This paper cites World Model on Million-Length Video And Language With Blockwise RingAttention.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos World Model on Million-Length Video And Language With Blockwise RingAttention

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.631572Z

Source-reported events for the cited work

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Observation b941f491-f909-4c8a-981d-78383969674f · outbound

This paper cites Video frame synthesis using deep voxel flow.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Video frame synthesis using deep voxel flow

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:11:54.758689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e8f5b1d6-03ca-43bb-bde2-bd06d94cbc77 · outbound

This paper cites Vdt: General-purpose video diffusion transformers via mask modeling.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Vdt: General-purpose video diffusion transformers via mask modeling

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:11:54.738155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation be619297-449c-4bae-803a-08a87feded31 · outbound

This paper cites Wovogen: World volume-aware diffusion for con- trollable multi-camera driving scene generation.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Wovogen: World volume-aware diffusion for con- trollable multi-camera driving scene generation

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:11:54.719005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4a7dd1c6-ebd6-44a8-a51b-29eedd3a59fd · outbound

This paper cites Masa-sr: Matching acceleration and spatial adaptation for reference-based image super-resolution.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Masa-sr: Matching acceleration and spatial adaptation for reference-based image super-resolution

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:11:54.701181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e18c1ab8-b42a-4b92-b71e-076cb7290abe · outbound

This paper cites VideoFusion: Decomposed Diffusion Models for High-Quality Video Generation.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos VideoFusion: Decomposed Diffusion Models for High-Quality Video Generation

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.676730Z

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Observation 81c6410c-c77a-4556-aead-686ffd165184 · outbound

This paper cites Open-MAGVIT2: An Open-Source Project Toward Democratizing Auto-regressive Visual Generation.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Open-MAGVIT2: An Open-Source Project Toward Democratizing Auto-regressive Visual Generation

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.684577Z

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Observation 9088f5d0-dca2-45db-8211-2d57682a1602 · outbound

This paper cites A Survey on Future Frame Synthesis: Bridging Deterministic and Generative Approaches.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos A Survey on Future Frame Synthesis: Bridging Deterministic and Generative Approaches

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.700387Z

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Observation 4d50a6da-060d-485c-a502-b4c4407616d5 · outbound

This paper cites 4m: Massively multimodal masked modeling.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos 4m: Massively multimodal masked modeling

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:11:54.682921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ec682287-68c2-4a2d-871c-3ea251d598b7 · outbound

This paper cites A review on deep learning techniques for video prediction.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos A review on deep learning techniques for video prediction

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:11:54.659454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0376c388-34c1-46f2-96e1-f57eb5b4fd79 · outbound

This paper cites Training lan- guage models to follow instructions with human feedback.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Training lan- guage models to follow instructions with human feedback

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:11:54.641719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9a21298a-3ac2-4870-82fe-0f3903b17733 · outbound

This paper cites Scalable diffusion models with transformers.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Scalable diffusion models with transformers

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.731052Z

Source-reported events for the cited work

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Observation 387405a6-6961-4e37-93ee-cf01d3337e85 · outbound

This paper cites Movie Gen: A Cast of Media Foundation Models.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Movie Gen: A Cast of Media Foundation Models

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.736838Z

Source-reported events for the cited work

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Observation f2d64baf-3c1d-4ac9-a43d-998b13696700 · outbound

This paper cites Improving language understanding by generative pre-training.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Improving language understanding by generative pre-training

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.742098Z

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Observation 86b41685-ca24-4e5a-8347-92e04007008a · outbound

This paper cites Zero-shot text-to-image generation.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Zero-shot text-to-image generation

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.749873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 91fe2c47-21cc-4c6b-85d2-13b1e42c3cec · outbound

This paper cites Gen- erating diverse high-fidelity images with vq-vae-2.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Gen- erating diverse high-fidelity images with vq-vae-2

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.755863Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f833eb71-60a7-43a4-b0b7-1fb6dd4da5ba · outbound

This paper cites High-resolution image syn- thesis with latent diffusion models.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos High-resolution image syn- thesis with latent diffusion models

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.761573Z

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Observation 45c0fdc8-1700-4991-99ee-3e81c1b30df3 · outbound

This paper cites Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.768454Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 432f6f19-dbe9-4d43-9392-c7f7c167daa0 · outbound

This paper cites Emu: Generative pretraining in multimodality.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Emu: Generative pretraining in multimodality

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:11:54.556717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 72a91f2a-6f3f-45f1-85ac-e556f1ffec2d · outbound

This paper cites Generative multimodal models are in-context learners.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Generative multimodal models are in-context learners

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.779648Z

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Observation d3f95508-5abb-4f43-9241-174b7b59b373 · outbound

This paper cites HART: Efficient Visual Generation with Hybrid Autoregressive Transformer.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos HART: Efficient Visual Generation with Hybrid Autoregressive Transformer

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.786214Z

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Observation 06f97568-33f6-4f54-918c-bbe14c87f65b · outbound

This paper cites Chameleon: Mixed-Modal Early-Fusion Foundation Models.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Chameleon: Mixed-Modal Early-Fusion Foundation Models

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.795799Z

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Observation 4ae9bebc-c9d0-4e2c-ad21-16b3724a10fd · outbound

This paper cites Raft: Recurrent all-pairs field transforms for optical flow.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Raft: Recurrent all-pairs field transforms for optical flow

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.806232Z

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Observation 9f863bbd-ef95-49b8-a71c-3976eab1d981 · outbound

This paper cites Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.814236Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a2ad54c0-dac9-4aa3-9ef8-89c5adbcd3f2 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos LLaMA: Open and Efficient Foundation Language Models

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.821530Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3134ff7a-5747-4adb-9dbb-0cce5ab31776 · outbound

This paper cites Towards Accurate Generative Models of Video: A New Metric & Challenges.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Towards Accurate Generative Models of Video: A New Metric & Challenges

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.828747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ad0e2a8-cb1d-4646-b66b-af36bc7e301b · outbound

This paper cites Diffusion Models Are Real-Time Game Engines.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Diffusion Models Are Real-Time Game Engines

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.838508Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ebb31694-1b4e-4ec6-98d8-dc36c9b489a5 · outbound

This paper cites Neural discrete representation learning.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Neural discrete representation learning

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:11:54.502833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5dae021c-4081-4c80-a806-e87ef27af093 · outbound

This paper cites Attention is all you need.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Attention is all you need

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:11:54.482705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b2524ef3-cb1c-41f2-ae34-6cfbcf6e7f82 · outbound

This paper cites Phenaki: Variable length video generation from open domain textual descriptions.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Phenaki: Variable length video generation from open domain textual descriptions

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:11:54.460023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f7ef387e-09e9-4216-a172-44d5f050b649 · outbound

This paper cites Images speak in images: A generalist painter for in-context visual learning.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Images speak in images: A generalist painter for in-context visual learning

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:11:54.433568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation bbd0dc0f-4b8a-4ba5-a6eb-025be1336b39 · outbound

This paper cites Seggpt: Towards seg- menting everything in context.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Seggpt: Towards seg- menting everything in context

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:11:54.411342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation bbe938da-b11d-4d50-9499-f02f52d11f18 · outbound

This paper cites DriveDreamer: Towards Real-world-driven World Models for Autonomous Driving.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos DriveDreamer: Towards Real-world-driven World Models for Autonomous Driving

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.887583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b25c7dc0-b0de-4c3f-86ac-43360c96536d · outbound

This paper cites Emu3: Next-Token Prediction is All You Need.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Emu3: Next-Token Prediction is All You Need

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.894742Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 93b6d96f-b5d6-4e76-836a-478f3bef1e7e · outbound

This paper cites InternVideo: General Video Foundation Models via Generative and Discriminative Learning.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos InternVideo: General Video Foundation Models via Generative and Discriminative Learning

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.903306Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c1f1047c-6953-4c04-a97b-2443903b5a73 · outbound

This paper cites Driving into the future: Multiview visual forecasting and planning with world model for au- tonomous driving.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Driving into the future: Multiview visual forecasting and planning with world model for au- tonomous driving

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:11:54.390480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0353e3cb-5f5d-43f8-800c-3a15b953a808 · outbound

This paper cites InternVideo2: Scaling Foundation Models for Multimodal Video Understanding.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos InternVideo2: Scaling Foundation Models for Multimodal Video Understanding

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.916995Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f3383fad-0396-41ba-885f-78bf3f574bc7 · outbound

This paper cites Loong: Generating Minute-level Long Videos with Autoregressive Language Models.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Loong: Generating Minute-level Long Videos with Autoregressive Language Models

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.923496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d5edc8c8-6d9d-4a9a-bb1d-5a4912036a76 · outbound

This paper cites Panacea: Panoramic and controllable video generation for autonomous driving.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Panacea: Panoramic and controllable video generation for autonomous driving

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:11:54.369075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 01d54d45-0ad7-40c0-ae53-ce0738ec8867 · outbound

This paper cites Motionrnn: A flexible model for video prediction with spacetime-varying motions.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Motionrnn: A flexible model for video prediction with spacetime-varying motions

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:11:54.351544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 474787cb-7397-45d6-8fb9-952af983f087 · outbound

This paper cites Tune-a-video: One-shot tuning of image diffusion models for text-to-video generation.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Tune-a-video: One-shot tuning of image diffusion models for text-to-video generation

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:11:54.333880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8785395c-1dd5-455d-859f-91a2c49d1ece · outbound

This paper cites Simmim: A simple framework for masked image modeling.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Simmim: A simple framework for masked image modeling

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:11:54.312868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation cb7a6224-dec5-4a3c-a09c-fdc8f3267fa7 · outbound

This paper cites A survey on video diffusion models.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos A survey on video diffusion models

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.961351Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f542c90-edc6-4cd2-a530-3631946b29a8 · outbound

This paper cites VideoGPT: Video Generation using VQ-VAE and Transformers.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos VideoGPT: Video Generation using VQ-VAE and Transformers

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.966047Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3fd68668-8fc2-4a1a-8249-076c5c3ac68a · outbound

This paper cites Generalized predictive model for autonomous driving.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Generalized predictive model for autonomous driving

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:11:54.283229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3fa20282-9e5c-49e4-a080-8d698d887d38 · outbound

This paper cites ZeroSmooth: Training-free Diffuser Adaptation for High Frame Rate Video Generation.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos ZeroSmooth: Training-free Diffuser Adaptation for High Frame Rate Video Generation

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.975570Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 93e4470a-d5db-42e7-b682-40b085b4382f · outbound

This paper cites CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.981361Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2681ddb4-6280-4c1c-a05c-566d7c7f3e4e · outbound

This paper cites CAR: Controllable Autoregressive Modeling for Visual Generation.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos CAR: Controllable Autoregressive Modeling for Visual Generation

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.986030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 99935dfd-3834-4960-97ab-c6efc4be1713 · outbound

This paper cites Bdd100k: A diverse driving dataset for heterogeneous multitask learning.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Bdd100k: A diverse driving dataset for heterogeneous multitask learning

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:11:54.261141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a66a9b79-569b-4714-b037-b236bf54604b · outbound

This paper cites Magvit: Masked generative video transformer.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Magvit: Masked generative video transformer

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:11:54.241365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e78a231d-688f-4d03-b621-7172f3bf7ca3 · outbound

This paper cites Language model beats diffusion - tokenizer is key to visual generation.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Language model beats diffusion - tokenizer is key to visual generation

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:11:54.223917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0853c036-e229-4b1d-ba9e-698b9183813e · outbound

This paper cites An image is worth 32 tokens for reconstruction and generation.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos An image is worth 32 tokens for reconstruction and generation

Reference 86

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:53.009061Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0a71ca33-a143-4d94-8ea9-a019105aec49 · outbound

This paper cites DriveDreamer-2: LLM-Enhanced World Models for Diverse Driving Video Generation.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos DriveDreamer-2: LLM-Enhanced World Models for Diverse Driving Video Generation

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:53.030836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc635933-a5f7-40e7-afa8-d2599f9f151d · outbound

This paper cites Image and Video Tokenization with Binary Spherical Quantization.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Image and Video Tokenization with Binary Spherical Quantization

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:53.036778Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 49cce8df-535f-4631-b10f-2d6b423952ab · outbound

This paper cites Movq: Modulating quantized vectors for high- fidelity image generation.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Movq: Modulating quantized vectors for high- fidelity image generation

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:11:54.192254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f4beb73a-b1fd-4991-adc4-d3ec2691415f · outbound

This paper cites Crossnet: An end-to-end reference-based super reso- lution network using cross-scale warping.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Crossnet: An end-to-end reference-based super reso- lution network using cross-scale warping

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:11:54.165996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 31913af0-2f91-4319-9aca-d64d0373afba · outbound

This paper cites Unicode: Learning a unified codebook for multimodal large language models.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos Unicode: Learning a unified codebook for multimodal large language models

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:11:54.134840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers