Paper Citation Record · LEDGER

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting

As of 7 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 3 inbound Pith citation observations for arXiv:2507.09144.

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

pith.paper-citation-record.v1
2507.09144 v2

Coverage vector

measured 62 of 62 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:08:54.630490Z

measured 65 of 65 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 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T06:04:23.964735Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T06:04:21.611097Z

Reference resolution

62 of 62 outbound references displayed

verified exact0
verified fuzzy54
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2bbb9c59-7659-4e8c-b65c-7d0c19f7301d · outbound

This paper cites GPT-4 Technical Report.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting GPT-4 Technical Report

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 66e84cc4-ba7a-4fea-87e8-4649dd5ce474 · outbound

This paper cites Cosmos world foundation model platform for physical ai.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Cosmos world foundation model platform for physical ai

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:09:05.081203Z

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 965e659d-8f89-4c29-a8c4-1a91d51690e3 · outbound

This paper cites V-jepa 2: Self- supervised video models enable understanding, prediction and planning.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting V-jepa 2: Self- supervised video models enable understanding, prediction and planning

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:09:04.858535Z

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 e18bab8f-8330-4d94-b8d7-08db64eae7e1 · outbound

This paper cites Semantickitti: A dataset for semantic scene understanding of lidar sequences.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Semantickitti: A dataset for semantic scene understanding of lidar sequences

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:09:04.637797Z

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 d138711c-cb41-429a-806c-385803b99432 · outbound

This paper cites The lov ´asz-softmax loss: A tractable surrogate for the optimization of the intersection-over-union measure in neural networks.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting The lov ´asz-softmax loss: A tractable surrogate for the optimization of the intersection-over-union measure in neural networks

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:09:04.395568Z

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 222df20f-8547-4aaf-8c8a-44d37659da11 · outbound

This paper cites Lang, Sourabh V ora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Gi- ancarlo Baldan, and Oscar Beijbom.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Lang, Sourabh V ora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Gi- ancarlo Baldan, and Oscar Beijbom

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:09:04.147704Z

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 30610dcb-f2ad-4225-ae5c-3319f977822f · outbound

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

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Taming transformers for high-resolution image synthesis

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:09:03.950736Z

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 6cb1d39a-9ec5-4da8-959d-fbb62f2def67 · outbound

This paper cites A survey of world models for autonomous driving.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting A survey of world models for autonomous driving

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:09:03.829784Z

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 69a33bb2-4a40-43c9-bddf-56f726d7088d · outbound

This paper cites Magicdrive: Street view generation with diverse 3d geometry control.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Magicdrive: Street view generation with diverse 3d geometry control

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:09:03.709724Z

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 65c97ca3-6e9a-4349-a51e-cf2bedf367a4 · outbound

This paper cites Vista: A generalizable driving world model with high fidelity and versatile controllability.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Vista: A generalizable driving world model with high fidelity and versatile controllability

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:09:03.536278Z

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 69b499b6-93b8-40fa-9686-373f74471843 · outbound

This paper cites DOME: Taming Diffusion Model into High-Fidelity Controllable Occupancy World Model.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting DOME: Taming Diffusion Model into High-Fidelity Controllable Occupancy World Model

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T18:08:50.127134Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b62e77aa-7eca-46f6-9bce-74fd1ac180f8 · outbound

This paper cites BEVDet: High-performance Multi-camera 3D Object Detection in Bird-Eye-View.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting BEVDet: High-performance Multi-camera 3D Object Detection in Bird-Eye-View

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T18:08:50.235191Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b5f1f833-cbcc-475b-80a4-ec8076d79f0e · outbound

This paper cites Tri-perspective view for vision-based 3d se- mantic occupancy prediction.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Tri-perspective view for vision-based 3d se- mantic occupancy prediction

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:09:03.399408Z

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 2f1c8941-a1f8-45af-8b68-6128e989fd7c · outbound

This paper cites Differentiable raycasting for self- supervised occupancy forecasting.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Differentiable raycasting for self- supervised occupancy forecasting

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:09:03.272688Z

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 743d97d8-8b93-4b63-979b-e20815fa1e63 · outbound

This paper cites Point cloud forecasting as a proxy for 4d occupancy forecast- ing.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Point cloud forecasting as a proxy for 4d occupancy forecast- ing

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:09:03.143906Z

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 c08a5008-6392-4e0e-8251-69842482cb4c · outbound

This paper cites Pointpillars: Fast encoders for object detection from point clouds.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Pointpillars: Fast encoders for object detection from point clouds

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:09:02.998009Z

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 82b2bad3-c536-47cb-a5b6-92c6fa2c0a5d · outbound

This paper cites Autoregressive image generation using resid- ual quantization.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Autoregressive image generation using resid- ual quantization

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:09:02.760488Z

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 7f6b9285-69a5-400f-b4d2-06beacf22cbe · outbound

This paper cites Uniscene: Unified occupancy-centric driving scene generation.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Uniscene: Unified occupancy-centric driving scene generation

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:09:02.498928Z

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 7e130820-8fb4-4571-98c5-9f8758968697 · outbound

This paper cites Bevstereo: Enhancing depth estimation in multi-view 3d object detection with temporal stereo.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Bevstereo: Enhancing depth estimation in multi-view 3d object detection with temporal stereo

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:09:02.228951Z

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 a25f3e61-c40e-45d0-b959-15d23045e2b6 · outbound

This paper cites Bevdepth: Acquisition of reliable depth for multi-view 3d object detec- tion.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Bevdepth: Acquisition of reliable depth for multi-view 3d object detec- tion

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:09:01.997157Z

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 34ebb596-8c32-4c92-a71f-dd79da3ea0dd · outbound

This paper cites V oxformer: Sparse voxel transformer for camera- based 3d semantic scene completion.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting V oxformer: Sparse voxel transformer for camera- based 3d semantic scene completion

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:09:01.753154Z

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 e88a43db-e0d1-4b78-90db-45eeeac41333 · outbound

This paper cites Bevformer: Learning bird’s-eye-view representation from multi-camera images via spatiotemporal transformers.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Bevformer: Learning bird’s-eye-view representation from multi-camera images via spatiotemporal transformers

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:09:01.507827Z

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 54451612-7eee-4b13-af85-73dd2aa7caf2 · outbound

This paper cites Fb-occ: 3d occupancy prediction based on forward-backward view transformation.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Fb-occ: 3d occupancy prediction based on forward-backward view transformation

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:09:01.369519Z

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 83c3227f-c3fe-448b-b16c-bac86c11e6c0 · outbound

This paper cites Stcocc: Sparse spatial-temporal cascade renova- tion for 3d occupancy and scene flow prediction.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Stcocc: Sparse spatial-temporal cascade renova- tion for 3d occupancy and scene flow prediction

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:09:01.219357Z

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 d1d715e2-b9ae-429c-9bdd-dd3b1685f073 · outbound

This paper cites Feature pyramid networks for object detection.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Feature pyramid networks for object detection

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:09:00.962012Z

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 61e59656-1b88-428f-ae1e-98855dbfa616 · outbound

This paper cites Sparsebev: High-performance sparse 3d object detec- tion from multi-camera videos.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Sparsebev: High-performance sparse 3d object detec- tion from multi-camera videos

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:09:00.821938Z

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 25fc74c4-001e-41fb-a08d-66a1b61921aa · outbound

This paper cites Decoupled Weight Decay Regularization.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Decoupled Weight Decay Regularization

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T18:08:52.036255Z

Source-reported events for the cited work

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Observation 6f43300d-16b0-4564-9856-629564ac49a0 · outbound

This paper cites Self-supervised point cloud prediction using 3d spatio-temporal convolutional networks.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Self-supervised point cloud prediction using 3d spatio-temporal convolutional networks

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:09:00.628992Z

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 f9f9068e-3c70-45fa-9962-bfbf5778fb65 · outbound

This paper cites Uniworld: Autonomous driving pre-training via world models.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Uniworld: Autonomous driving pre-training via world models

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:09:00.442668Z

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 8ec25494-0bef-441c-8f0e-d8bd45c3547c · outbound

This paper cites Driveworld: 4d pre-trained scene understanding via world models for autonomous driving.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Driveworld: 4d pre-trained scene understanding via world models for autonomous driving

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:09:00.271810Z

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 f7c78b6c-5e7a-49f7-8015-1e195d58c065 · outbound

This paper cites Renderocc: Vision- centric 3d occupancy prediction with 2d rendering supervi- sion.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Renderocc: Vision- centric 3d occupancy prediction with 2d rendering supervi- sion

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:09:00.141947Z

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 0adca95e-b7c8-49ec-951c-7a4af22a493d · outbound

This paper cites Scalable diffusion models with transformers.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Scalable diffusion models with transformers

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:08:59.939166Z

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 d14a39b2-6cb5-430b-8cf1-ec119baabb23 · outbound

This paper cites Gener- ating diverse high-fidelity images with vq-vae-2.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Gener- ating diverse high-fidelity images with vq-vae-2

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:08:59.761346Z

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 33feea60-fcd3-4d54-a652-beae61e9d8bd · outbound

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

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting High-resolution image synthesis with latent diffusion models

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-06T18:08:52.670827Z

Source-reported events for the cited work

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Observation 099d5316-3ec0-4356-8e00-1c683c10e7b3 · outbound

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

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting High-resolution image synthesis with latent diffusion models

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:08:59.640948Z

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 56daf1cb-2efe-4f22-b982-5708c729dd9b · outbound

This paper cites Pointr- cnn: 3d object proposal generation and detection from point cloud.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Pointr- cnn: 3d object proposal generation and detection from point cloud

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:08:59.534102Z

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 db5da3c2-a0fa-45ce-833e-f30d6135bdf8 · outbound

This paper cites Scalability in perception for autonomous driving: Waymo open dataset.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Scalability in perception for autonomous driving: Waymo open dataset

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:08:59.360467Z

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 57067620-3d17-407b-aae0-014d1c8ded3f · outbound

This paper cites Vidtok: A versatile and open-source video tokenizer.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Vidtok: A versatile and open-source video tokenizer

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:08:59.215295Z

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 7a74403d-91a4-4a80-bb60-32c6fa72906d · outbound

This paper cites Visual autoregressive modeling: Scalable image generation via next-scale prediction.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Visual autoregressive modeling: Scalable image generation via next-scale prediction

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:08:59.073376Z

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 21565967-1c02-42c9-b6fc-a13e8aad039d · outbound

This paper cites Occ3d: A large-scale 3d occupancy prediction benchmark for au- tonomous driving.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Occ3d: A large-scale 3d occupancy prediction benchmark for au- tonomous driving

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:08:58.911047Z

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 099436e3-04e4-439d-aa0b-bce8c8bed48a · outbound

This paper cites Neural discrete representation learning.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Neural discrete representation learning

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:08:58.743975Z

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 04e126c0-afaa-4328-ac32-2f3c4c46b1d5 · outbound

This paper cites Attention is all you need.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Attention is all you need

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:08:58.609298Z

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 bccb78db-3114-4aa3-abae-3579711fe1bc · outbound

This paper cites Omnitokenizer: A joint image-video tokenizer for visual generation.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Omnitokenizer: A joint image-video tokenizer for visual generation

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:08:58.452120Z

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 f459aa87-5b1d-4d6e-9b2d-05fce9a823b5 · outbound

This paper cites OccSora: 4D Occupancy Generation Models as World Simulators for Autonomous Driving.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting OccSora: 4D Occupancy Generation Models as World Simulators for Autonomous Driving

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-06T18:08:53.539429Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c7f01f57-31fe-47f7-9af9-073e815af061 · outbound

This paper cites Drivedreamer: Towards real-world- drive world models for autonomous driving.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Drivedreamer: Towards real-world- drive world models for autonomous driving

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:08:58.317739Z

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 110888b1-8ef1-485e-afcd-c52478dc0446 · outbound

This paper cites Occllama: An occupancy- language-action generative world model for autonomous driv- ing.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Occllama: An occupancy- language-action generative world model for autonomous driv- ing

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:08:58.179254Z

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 e8361453-a2cb-467a-aabb-d712ebffad80 · outbound

This paper cites Inverting the pose forecasting pipeline with spf2: Sequential pointcloud forecasting for sequential pose forecasting.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Inverting the pose forecasting pipeline with spf2: Sequential pointcloud forecasting for sequential pose forecasting

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:08:58.033467Z

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 a4e81d92-c85a-463c-8ed0-9110de2c7fff · outbound

This paper cites ivideogpt: Interactive videogpts are scalable world models.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting ivideogpt: Interactive videogpts are scalable world models

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:08:57.800415Z

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 3c105349-79a2-4657-a197-2c3e912ed02a · outbound

This paper cites Occ-llm: Enhancing autonomous driving with occupancy-based large language models.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Occ-llm: Enhancing autonomous driving with occupancy-based large language models

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:08:57.655793Z

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 064180a0-e7b7-4992-8186-da7c2a7cb1de · outbound

This paper cites Videogpt: Video generation using vq-vae and transform- ers.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Videogpt: Video generation using vq-vae and transform- ers

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:08:57.483539Z

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 694925b3-ab48-4c1f-956c-1f7ab4d310c1 · outbound

This paper cites Renderworld: World model with self-supervised 3d label.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Renderworld: World model with self-supervised 3d label

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:08:57.138598Z

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 2d2f8d2f-4caf-4d18-91d9-b125fae29c9a · outbound

This paper cites Bevformer v2: Adapting modern image backbones to bird’s-eye-view recognition via perspective su- pervision.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Bevformer v2: Adapting modern image backbones to bird’s-eye-view recognition via perspective su- pervision

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:08:56.805746Z

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 e977cd88-d0f1-4faf-af0c-27e452e22984 · outbound

This paper cites Driving in the occupancy world: Vision-centric 4d occupancy forecasting and planning via world models for autonomous driving.AAAI,.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Driving in the occupancy world: Vision-centric 4d occupancy forecasting and planning via world models for autonomous driving.AAAI,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:08:56.536961Z

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 8b6a7c64-83c9-49c0-9ef6-8062a3b23f88 · outbound

This paper cites Magvit: Masked generative video transformer.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Magvit: Masked generative video transformer

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:08:56.185791Z

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 77cf7902-228e-4d73-a16a-b73cc266e453 · outbound

This paper cites An Efficient Occupancy World Model via Decoupled Dynamic Flow and Image-assisted Training.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting An Efficient Occupancy World Model via Decoupled Dynamic Flow and Image-assisted Training

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-06T18:08:54.319827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 78fd15a8-b6d8-49f2-8ae5-b05f35aad011 · outbound

This paper cites Copilot4d: Learning unsupervised world models for autonomous driving via discrete diffusion.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Copilot4d: Learning unsupervised world models for autonomous driving via discrete diffusion

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:08:55.948100Z

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 c46c6f49-6e33-4b5c-86c4-8484eba1f7f1 · outbound

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

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting DriveDreamer-2: LLM-Enhanced World Models for Diverse Driving Video Generation

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-06T18:08:54.392162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 127bba40-acbf-4a51-8fbb-e1c9940887e5 · outbound

This paper cites Cv-vae: A compatible video vae for latent generative video models.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Cv-vae: A compatible video vae for latent generative video models

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:08:55.684773Z

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 53cbfdfe-6fb4-43e3-ab81-33f0a834df97 · outbound

This paper cites Occworld: Learning a 3d occupancy world model for autonomous driving.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Occworld: Learning a 3d occupancy world model for autonomous driving

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:08:55.372362Z

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 16c40c42-07a2-4d24-9052-96b0e4c25d69 · outbound

This paper cites Hitvideo: Hierarchical tokenizers for enhancing text-to- video generation with autoregressive large language models.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Hitvideo: Hierarchical tokenizers for enhancing text-to- video generation with autoregressive large language models

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:08:55.194296Z

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 3d658106-c657-4d36-a2cd-79356caeb59a · outbound

This paper cites Scaling the codebook size of vq-gan to 100,000 with a utilization rate of 99%.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Scaling the codebook size of vq-gan to 100,000 with a utilization rate of 99%

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:08:55.034751Z

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 f72cfb80-31fc-4cc4-b8a8-f94862811795 · outbound

This paper cites Deformable detr: Deformable transformers for end-to-end object detection.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting Deformable detr: Deformable transformers for end-to-end object detection

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:08:54.873947Z

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

Observation 6e1c4be7-4d62-43e7-9758-7e2c00ad752c · inbound

3D and 4D World Modeling: A Survey cites this paper.

3D and 4D World Modeling: A Survey $I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting

Reference 142

Resolution: unresolved; no resolver link, observed 2026-08-05T06:04:23.964735Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f43675e7-76f5-40d7-a1c2-e3fcd4bb03a6 · inbound

SparseWorld-TC: Trajectory-Conditioned Sparse Occupancy World Model cites this paper.

SparseWorld-TC: Trajectory-Conditioned Sparse Occupancy World Model $I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-17T05:29:05.040869Z

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 e607822e-c87d-47a0-b335-f9067297f13b · inbound

OWMDrive: Causality-Aware End-to-End Autonomous Driving via 4D Occupancy World Model cites this paper.

OWMDrive: Causality-Aware End-to-End Autonomous Driving via 4D Occupancy World Model $I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-06-30T06:04:21.612613Z

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.