Pith. sign in

Paper Citation Record · LEDGER

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model

As of 10 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 4 inbound Pith citation observations for arXiv:2506.13260.

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

pith.paper-citation-record.v1
2506.13260 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:41:32.920263Z

measured 41 of 41 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T06:04:36.170867Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-17T05:29:04.993194Z

Reference resolution

37 of 37 outbound references displayed

  • verified exact1
  • verified fuzzy12
  • unresolved23
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1ef9243d-17ff-49c9-a1ba-2d2d2a528bc6 · outbound

This paper cites Uno: Unsupervised occupancy fields for perception and forecasting.

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model Uno: Unsupervised occupancy fields for perception and forecasting

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:41:35.527513Z

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=2026-08-07T00:41:29.658172Z digest=sha256:74334bbc7a8d8f9108e305a1fb80d43aa5f54d50a3c2dc4b148cd726d5730d52

Observation 1e80fe38-49f3-43f3-b335-d9376d8b6df4 · outbound

This paper cites nuscenes: A multimodal dataset for autonomous driving.

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model nuscenes: A multimodal dataset for autonomous driving

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-07T00:41:29.799682Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:41:29.799682Z digest=sha256:424988669c51955fe427c8587f0e08b715df1000bee1ececedc4b7f6b7bcf9f0

Observation 5026a570-a1fa-4589-98e4-01b1c8fd1085 · outbound

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

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model DOME: Taming Diffusion Model into High-Fidelity Controllable Occupancy World Model

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-07T00:41:29.912088Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:41:29.912088Z digest=sha256:cf294bcac12f29cf00bf1bbebc20cf718ecd166dc024881762155c5f6a2a11f9

Observation 23bd03a3-2306-4826-a5cf-8cce9975a87b · outbound

This paper cites Denoising diffusion probabilistic models.

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model Denoising diffusion probabilistic models

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T00:41:30.033977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:41:30.033977Z digest=sha256:101e7d46bf45840ade1fa4cb420938df0027041ef7b4a55178337c10e2327c5b

Observation 3be2261a-62f1-43cc-8787-89e91c4ce275 · outbound

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

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model GAIA-1: A Generative World Model for Autonomous Driving

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T00:41:30.177692Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:41:30.177692Z digest=sha256:feee66ec5a9354e6626b35e911bad00af318d21c82680d84c254b61d006e1876

Observation 5938915a-5176-40c5-8922-985cd69860db · outbound

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

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model BEVDet: High-performance Multi-camera 3D Object Detection in Bird-Eye-View

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-07T00:41:30.277622Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:41:30.277622Z digest=sha256:ccd4df75b5b932e7932ceef1c36215596f74977e6ff92923a65207570c225127

Observation 40267931-cfdb-43d1-93fe-1fb6c9c34eff · outbound

This paper cites Occvar: Scalable 4d occupancy prediction via next-scale prediction.

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model Occvar: Scalable 4d occupancy prediction via next-scale prediction

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:41:35.393918Z

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=2026-08-07T00:41:30.359584Z digest=sha256:73318f74cd3e6b7da7a1e9f7e374844c64d7c6b88bd3cf8ba04710f88c194b1c

Observation 9f2df0a0-a8fe-4f4f-8f2c-ec4ffdeb39ad · outbound

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

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model Point cloud forecasting as a proxy for 4d occupancy forecasting

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:41:35.244590Z

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=2026-08-07T00:41:30.492956Z digest=sha256:a137b8d943ce95ed0297a8d7d40acc66976624bccf4a0bbca7ce12f4d55bc5cd

Observation 9036dc7e-ae23-4b54-a8be-395b0e94fbf2 · outbound

This paper cites UniScene: Unified Occupancy-centric Driving Scene Generation.

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model UniScene: Unified Occupancy-centric Driving Scene Generation

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T00:41:30.578596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:41:30.578596Z digest=sha256:986c66a3a5deae0ff01ab6dd7120781e18c2ffb7b3f62919b16e35f86921fd68

Observation ed1319a7-e84c-4160-ac10-4c62229408a8 · outbound

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

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model Bevstereo: Enhancing depth estimation in multi-view 3d object detection with temporal stereo

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:41:35.094727Z

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=2026-08-07T00:41:30.655057Z digest=sha256:146764573a5475c7a8341b5f61389a03e2c30444fe1475f540dbab812f07ae10

Observation b75c20ac-9734-4f78-8c5f-350876d716c1 · outbound

This paper cites Hunyuan-DiT: A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding.

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model Hunyuan-DiT: A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T00:41:30.764087Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:41:30.764087Z digest=sha256:8924da18c5b261b0bd5f7a2ffaefe1b7e1151579b35c557e737cb017d90c2bb3

Observation 6b32653c-63f8-448d-afea-eb52cc8b24a2 · outbound

This paper cites an unresolved cited work.

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model Unresolved cited work

Reference 14

Resolution
unresolved
raw_fallback, observed 2026-08-07T00:41:34.923737Z

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=2026-08-07T00:41:30.819940Z digest=sha256:d68d7aa8c66d39266c5c04e547e2fd1b5e95fbb4a34589190dd1e893e6266ec2

Observation d8523112-31a2-430d-ad35-c1ea6cc36bdc · outbound

This paper cites Lidar-based 4d occupancy completion and forecasting.

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model Lidar-based 4d occupancy completion and forecasting

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:41:34.780713Z

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=2026-08-07T00:41:30.922759Z digest=sha256:f42d48fa0fd687792bfead26eaaa8c5b36ff3b0ccc7f7c997e18640ef9aa5211

Observation ff3d10ac-f712-4be0-baa1-0702b1aef34f · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model Swin transformer: Hierarchical vision transformer using shifted windows

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:41:34.631422Z

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=2026-08-07T00:41:30.993218Z digest=sha256:ff9c0111a2d788f7c5f71daa2b8aba03649be34ccad13a7c37890ffc73b169ae

Observation cb16cb00-b0ab-492d-b326-127ad2376b87 · outbound

This paper cites Cam4docc: Benchmark for camera-only 4d occupancy forecasting in autonomous driving applications.

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model Cam4docc: Benchmark for camera-only 4d occupancy forecasting in autonomous driving applications

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:41:34.446495Z

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=2026-08-07T00:41:31.089755Z digest=sha256:5ab8421204e2b4c544c5ce488b38be274bdc9dfcf30bcc5e422c05138f5b1eca

Observation 0e88c693-6f6a-4b6a-b56e-0bfc6ebe90d6 · outbound

This paper cites Scalable diffusion models with transformers.

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model Scalable diffusion models with transformers

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-07T00:41:31.152713Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:41:31.152713Z digest=sha256:802147bb04096d805ea1c0fd5b734c119b82479b43c2cbdde403a69f397de6eb

Observation 8388be47-9b32-4b88-bb36-0cc6f0b61f36 · outbound

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

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model U-net: Convolutional networks for biomedical image segmentation

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-07T00:41:31.233467Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:41:31.233467Z digest=sha256:ee4ae79d4d54114b2c7d70df763ec53179af2be69655ffa878bf63e707a65873

Observation b07042ec-7c42-4c52-8012-a7ada70821cb · outbound

This paper cites Con- volutional lstm network: A machine learning approach for precipitation nowcasting.Advances in neural information processing systems, 28, 2015.

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model Con- volutional lstm network: A machine learning approach for precipitation nowcasting.Advances in neural information processing systems, 28, 2015

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:41:34.293248Z

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=2026-08-07T00:41:31.316384Z digest=sha256:c27b519db0484338e0eb503197d8905d6cc8a8aeb4415c4d1bd3899069ea28b4

Observation ecd96ce3-4e5e-4422-81a7-8677e99dfbc8 · outbound

This paper cites EFFOcc: Learning Efficient Occupancy Networks from Minimal Labels for Autonomous Driving.

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model EFFOcc: Learning Efficient Occupancy Networks from Minimal Labels for Autonomous Driving

Reference 21

Resolution
verified exact
local_arxiv, observed 2026-08-07T00:41:33.342438Z

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=2026-08-07T00:41:31.388456Z digest=sha256:6de5965bda2b3fa01608bbe0788017c2eece39ea23b96b8d9112d09a8ead1da2

Observation b2edc815-eae4-4716-bfa9-565217c5ce1e · outbound

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

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model Scalability in perception for autonomous driving: Waymo open dataset

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-07T00:41:31.431256Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:41:31.431256Z digest=sha256:fea66cb6b46c3e42e3d0e5f1f1ecb47707b1e85613d172a733c68a0f2f06b29e

Observation a2902f26-c002-46bd-800e-b44d371a5e74 · outbound

This paper cites Occ3d: A large-scale 3d occupancy prediction benchmark for autonomous driving.Advances in Neural Information Processing Systems, 36:64318–64330, 2023.

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model Occ3d: A large-scale 3d occupancy prediction benchmark for autonomous driving.Advances in Neural Information Processing Systems, 36:64318–64330, 2023

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-07T00:41:31.502360Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:41:31.502360Z digest=sha256:3e0b93c9d84ca023cb8b3c04add4b30193c831b437ac1ebb82ecb52116699780

Observation fcc4e28a-511b-4384-99fa-f7a9e89ab10b · outbound

This paper cites Neural discrete representation learning.

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model Neural discrete representation learning

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:41:34.160741Z

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=2026-08-07T00:41:31.590895Z digest=sha256:373528a511f7e67ca56781297a8d6af947ff28d3eb75d959a363027b1957e80a

Observation 8f80907e-0fa0-4c16-9a83-abe0be750e65 · outbound

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

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model Drivedreamer: Towards real-world-drive world models for autonomous driving

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:41:34.003630Z

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=2026-08-07T00:41:31.643933Z digest=sha256:5507e2e0be2079eb79d28e83f38cbc4ae04f2ab472bfac37b41614919f0d61b6

Observation b24975eb-15f8-4db8-90fa-0107338ff240 · outbound

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

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model Driving into the future: Multiview visual forecasting and planning with world model for autonomous driving

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-07T00:41:31.747234Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:41:31.747234Z digest=sha256:a11278ed8510056e777147773e918ab74ff905428f38f584baa249dc1c1c3429

Observation 76d42f60-53b5-4829-af22-485d6a7f8f97 · outbound

This paper cites OccLLaMA: An Occupancy-Language-Action Generative World Model for Autonomous Driving.

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model OccLLaMA: An Occupancy-Language-Action Generative World Model for Autonomous Driving

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-07T00:41:31.824261Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:41:31.824261Z digest=sha256:2986181107d7f3ff5be832d9a235a4d8dca94bf320bde45c112509a262fecdb3

Observation 2299b58a-7fd4-494a-b66c-cca830d5e328 · outbound

This paper cites Occ-LLM: Enhancing Autonomous Driving with Occupancy-Based Large Language Models.

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model Occ-LLM: Enhancing Autonomous Driving with Occupancy-Based Large Language Models

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-07T00:41:31.920937Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:41:31.920937Z digest=sha256:0184441c528a58e3bd1f4d6ab7b359398028eee50b2b2946fe9949c97430d043

Observation e324fb33-b147-4702-8af2-446469998f9f · outbound

This paper cites DrivingSphere: Building a High-fidelity 4D World for Closed-loop Simulation.

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model DrivingSphere: Building a High-fidelity 4D World for Closed-loop Simulation

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-07T00:41:32.020698Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:41:32.020698Z digest=sha256:bd1db3be40fba34423a36148e3e830702916514b4fb4b634791f18eda2ed335c

Observation 35dce14c-04aa-4d4e-affd-231a24ef1861 · outbound

This paper cites RenderWorld: World Model with Self-Supervised 3D Label.

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model RenderWorld: World Model with Self-Supervised 3D Label

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T00:41:32.077815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:41:32.077815Z digest=sha256:9df4ae123226e89cd95e83c18a208af05eb72066c8ed4580301ee94dd37b6901

Observation 8084a072-e6cd-4c3c-8020-5b6e790b3ed7 · outbound

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

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model Driving in the occupancy world: Vision-centric 4d occupancy forecasting and planning via world models for autonomous driving

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-07T00:41:32.218448Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:41:32.218448Z digest=sha256:6e1edd417433f7bcf745c8c581464256f0e7dc7161a4bee499e7b7fc80e811ac

Observation b09fa4af-e1ae-42bf-973b-f67b3cab838d · outbound

This paper cites Visual point cloud forecasting enables scalable autonomous driving.

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model Visual point cloud forecasting enables scalable autonomous driving

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:41:33.874937Z

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=2026-08-07T00:41:32.274960Z digest=sha256:3274e579fb762e32a7b6f0fb747a603f5a4555bd64dcf700cee03e7059652c5e

Observation 4bdaebea-710b-40e1-8aac-2a86e3bfb782 · outbound

This paper cites Visual point cloud forecasting enables scalable autonomous driving.

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model Visual point cloud forecasting enables scalable autonomous driving

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:41:33.721994Z

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=2026-08-07T00:41:32.389538Z digest=sha256:c80c45e5121d82136e9cfef0b072fb3d7d6df4485d904d15d4d9bdcbc3edb241

Observation f5103b9b-e2c5-402c-91de-4cca20beb151 · outbound

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

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model An Efficient Occupancy World Model via Decoupled Dynamic Flow and Image-assisted Training

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T00:41:32.473709Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:41:32.473709Z digest=sha256:360555c2e56f3421264f11afd4c43165427104114002fb08f994be39a0fa8625

Observation a7c31ae1-d053-4527-a444-2761f36aa56b · outbound

This paper cites Adding conditional control to text-to-image diffusion models.

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model Adding conditional control to text-to-image diffusion models

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-07T00:41:32.564579Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:41:32.564579Z digest=sha256:10e6399708f6afaf11c5ba798bf082408bac22033c1315e987b999c353e95c0a

Observation 2c4aa7fc-6db8-43f4-bf3f-f9eb089527c2 · outbound

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

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model Occworld: Learning a 3d occupancy world model for autonomous driving

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-07T00:41:32.673853Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:41:32.673853Z digest=sha256:0b84d119d02b7eb3bfb8fb17122ae9bc1fd230168bbfb1ca6b38293dabbfdfd7

Observation e822020c-1ebd-4949-9f5e-dfde32127267 · outbound

This paper cites Class-balanced Grouping and Sampling for Point Cloud 3D Object Detection.

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model Class-balanced Grouping and Sampling for Point Cloud 3D Object Detection

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T00:41:32.763719Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:41:32.763719Z digest=sha256:00bc40f3b57be6feee9b0d8e1f75c577484c469f14484d9f223ad6e8378fb1de

Observation 2f97d3a9-b35f-46c5-a999-0250bac3de4c · outbound

This paper cites Lidardm: Generative lidar simulation in a generated world.arXiv preprint arXiv:2404.02903, 2024.

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model Lidardm: Generative lidar simulation in a generated world.arXiv preprint arXiv:2404.02903, 2024

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T00:41:32.847230Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:41:32.847230Z digest=sha256:db4a7d8994517b4cc363cc2e5098d987799fc15e35562986f8cda6d879d484e4

Observation 4ecf20b1-8a5f-4fce-9f4b-bed09622016a · outbound

This paper cites For different size of world models, corresponding controlnet has half of the depth of the world model and uses the same parameters in each block.

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model For different size of world models, corresponding controlnet has half of the depth of the world model and uses the same parameters in each block

Reference 39

Resolution
malformed identifier
raw_fallback, observed 2026-08-07T00:41:33.573070Z

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=2026-08-07T00:41:32.920263Z digest=sha256:e40d18c074c39b3c1e586065e8b5db2633e57cfdb871233e32d35dee20acd301

Pith citing papers

Observation c1e4b33c-0f8b-4bc2-b534-8e7b828e8e02 · inbound

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

3D and 4D World Modeling: A Survey COME: Adding Scene-Centric Forecasting Control to Occupancy World Model

Reference 204

Resolution
unresolved
no resolver link, observed 2026-08-05T06:04:36.170867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T06:04:36.170867Z digest=sha256:c4db7cf40eba76fa51baf1d86f22b3a4ead5b29147190012899c8b56c2230abf

Observation 6e50bd6c-0505-4480-8137-bc9a2f7fbdce · inbound

A Comprehensive Survey on World Models for Embodied AI cites this paper.

A Comprehensive Survey on World Models for Embodied AI COME: Adding Scene-Centric Forecasting Control to Occupancy World Model

Reference 213

Resolution
unresolved
no resolver link, observed 2026-08-04T09:12:54.258372Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T09:12:54.258372Z digest=sha256:7f08539470cddafe358b46d1878641965963607f49bc5cb72761579dc8e0b3e4

Observation dc24a7c7-da98-4547-ab2e-a43b9b5810c0 · inbound

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

SparseWorld-TC: Trajectory-Conditioned Sparse Occupancy World Model COME: Adding Scene-Centric Forecasting Control to Occupancy World Model

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-05-17T05:29:04.995640Z

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=2026-05-17T05:26:34.859975Z digest=sha256:e6a72a73aff84914fb963af7354e82fccf4a4964784dc3d848233a17b2f92b9d

Observation ee12482f-2b22-4709-9e37-dc6bdc3156af · inbound

GEM: Generating LiDAR World Model via Deformable Mamba cites this paper.

GEM: Generating LiDAR World Model via Deformable Mamba COME: Adding Scene-Centric Forecasting Control to Occupancy World Model

Reference 41

Resolution
verified exact
arxiv_id, observed 2026-05-11T01:45:51.317260Z

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=2026-05-11T01:31:09.604703Z digest=sha256:6783ff5590add4235e44f9a0a743163adeea7239a6a54f3b408e6a6b6b654d2a