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Paper Citation Record · LEDGER

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting

As of 19 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2411.14169.

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

pith.paper-citation-record.v1
2411.14169 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T15:32:47.491471Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

42 of 42 outbound references displayed

  • verified exact3
  • verified fuzzy24
  • unresolved15
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3504bf93-38b5-4faa-9183-f56ef013a858 · outbound

This paper cites Monoscene: Monocular 3d semantic scene completion,.

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting Monoscene: Monocular 3d semantic scene completion,

Reference 1

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Unavailable: canonical work link unavailable.

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Observation 6bd4257c-386e-4249-857c-82b4ac9de964 · outbound

This paper cites Openoccupancy: A large scale benchmark for surrounding semantic occupancy perception,.

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting Openoccupancy: A large scale benchmark for surrounding semantic occupancy perception,

Reference 2

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Observation a42b20e5-74db-4914-b20a-29709dde10df · outbound

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

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting V oxformer: Sparse voxel transformer for camera- based 3d semantic scene completion,

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation e97cf924-ae70-4cf7-8a9c-02e156cd4401 · outbound

This paper cites Occformer: Dual-path transformer for vision-based 3d semantic occupancy prediction,.

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting Occformer: Dual-path transformer for vision-based 3d semantic occupancy prediction,

Reference 4

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raw_fallback, observed 2026-08-12T15:32:48.112358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T15:32:47.330485Z digest=sha256:717309e192f208a4fae7dcf219148f00d2eef39b6342c13be1bf5e71b8db3e60

Observation d1b76671-acec-4f60-ab64-08d61c12f981 · outbound

This paper cites Tri-perspective view for vision-based 3d semantic occupancy prediction,.

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting Tri-perspective view for vision-based 3d semantic occupancy prediction,

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation b0540709-bc74-4511-89ed-23c7b9fc5441 · outbound

This paper cites UniVision: A Unified Framework for Vision-Centric 3D Perception.

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting UniVision: A Unified Framework for Vision-Centric 3D Perception

Reference 6

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verified exact
local_arxiv, observed 2026-08-12T15:32:47.657378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 77361583-cf10-4faf-af81-19a7aea67e05 · outbound

This paper cites Selfocc: Self- supervised vision-based 3d occupancy prediction,.

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting Selfocc: Self- supervised vision-based 3d occupancy prediction,

Reference 7

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raw_fallback, observed 2026-08-12T15:32:48.085478Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 8b4704f1-e30c-4460-97cb-1b6010a83457 · outbound

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

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting Point cloud forecasting as a proxy for 4d occupancy forecasting,

Reference 8

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raw_fallback, observed 2026-08-12T15:32:48.071179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T15:32:47.346145Z digest=sha256:d219daa729a46516aaa55e61034167c91f65281467042e09adf4455fa7ab677d

Observation 53c91146-c23d-489b-a9bb-e9bd5225c775 · outbound

This paper cites Fiery: Future instance prediction in bird’s- eye view from surround monocular cameras,.

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting Fiery: Future instance prediction in bird’s- eye view from surround monocular cameras,

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T15:32:47.350850Z digest=sha256:467bc843b1497f9fe2fedf717a532828cb40e1d439ea298dcd8b2e116959015e

Observation 8e2e5854-e2ec-43f4-bb7a-75e9b9811088 · outbound

This paper cites Stretchbev: Stretching future instance prediction spatially and temporally,.

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting Stretchbev: Stretching future instance prediction spatially and temporally,

Reference 10

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raw_fallback, observed 2026-08-12T15:32:48.043986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T15:32:47.355081Z digest=sha256:094c801318272f0862c8070ab2f9d9f8c42b9b956767a01ce04fccc166391915

Observation e1c0e668-104f-4bf5-869b-c1c0e7c34e8f · outbound

This paper cites BEVerse: Unified Perception and Prediction in Birds-Eye-View for Vision-Centric Autonomous Driving.

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting BEVerse: Unified Perception and Prediction in Birds-Eye-View for Vision-Centric Autonomous Driving

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation bbf1f3a3-71fa-4ac5-9ede-45f77fd713c0 · outbound

This paper cites Powerbev: a powerful yet lightweight framework for instance pre- diction in bird’s-eye view,.

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting Powerbev: a powerful yet lightweight framework for instance pre- diction in bird’s-eye view,

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T15:32:47.364167Z digest=sha256:eef5f2491780ca37d2315aa8b5cdb29b95b3284658cd24754b87c6842b7dde56

Observation b74138f2-3edb-4cfe-bf88-651f0346d006 · outbound

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

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting Cam4docc: Benchmark for camera-only 4d occupancy forecasting in autonomous driving applications,

Reference 13

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raw_fallback, observed 2026-08-12T15:32:48.017388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T15:32:47.367421Z digest=sha256:5ba278d02cc0c3489407a86c006ed89898d26e76a118f100c071607b713ae7d6

Observation 4edcee08-3033-489e-a079-68d376116661 · outbound

This paper cites LiDAR-based 4D Occupancy Completion and Forecasting.

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting LiDAR-based 4D Occupancy Completion and Forecasting

Reference 14

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source=pdf_text observed=2026-08-12T15:32:47.371082Z digest=sha256:843cea15942514373fad70a5d7d4e2dacd8afbc02d9fd19d9615f13017474fb7

Observation c9f0c4f7-6362-4880-9d41-c6d0d83a38fa · outbound

This paper cites Surroundocc: Multi-camera 3d occupancy prediction for autonomous driving,.

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting Surroundocc: Multi-camera 3d occupancy prediction for autonomous driving,

Reference 15

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source=pdf_text observed=2026-08-12T15:32:47.374735Z digest=sha256:89756abc21a3c6b9d9e49ed2ef9257deac4708bc86d59fb02150fd3aec10208b

Observation 6be650c7-27bf-4108-add8-3a0acea9d373 · outbound

This paper cites UniOcc: Unifying Vision-Centric 3D Occupancy Prediction with Geometric and Semantic Rendering.

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting UniOcc: Unifying Vision-Centric 3D Occupancy Prediction with Geometric and Semantic Rendering

Reference 16

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-12T15:32:47.378279Z digest=sha256:0c38fe3772952a11626810a7fef8db072deeab6784f994d2c81aebadb59dc9c4

Observation 66315e7f-0155-4619-ae25-e7f3bae0a108 · outbound

This paper cites OccTransformer: Improving BEVFormer for 3D camera-only occupancy prediction.

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting OccTransformer: Improving BEVFormer for 3D camera-only occupancy prediction

Reference 17

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local_arxiv, observed 2026-08-12T15:32:47.609983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation b9c06948-281d-401c-ba0a-d4f721221958 · outbound

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

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting nuscenes: A multimodal dataset for autonomous driving,

Reference 18

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Observation 9dd517f9-b526-46f2-a5ab-a6da9b7d8b76 · outbound

This paper cites Lyft level 5 perception dataset 2020,.

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting Lyft level 5 perception dataset 2020,

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T15:32:47.390510Z digest=sha256:d1bb9a3aea322fe614ae652f7a52886a73e7bb2bdc87309b6f420f8d3d42e769

Observation 0ce5f56c-b18c-478f-964a-d3951c1ee42f · outbound

This paper cites Attention is all you need,.

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting Attention is all you need,

Reference 20

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-12T15:32:47.394461Z digest=sha256:b6dd0e875bc3fc4b94a75a990bc0f92e3dd3fd9f1c7e9abfe660b741fada89f1

Observation 8d3ba5ad-a8a3-4016-ab42-40125af21231 · outbound

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

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting Occ3d: A large-scale 3d occupancy prediction benchmark for autonomous driving,

Reference 21

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source=pdf_text observed=2026-08-12T15:32:47.398188Z digest=sha256:bfb434d412a934e7deaa3611e759037b8e20911caa581dbf544aa15b6682c81c

Observation 2e099d6b-5456-43dc-933d-a1bebf5da3ac · outbound

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

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting Bevformer: Learning bird’s-eye-view representation from multi-camera images via spatiotemporal transformers,

Reference 22

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raw_fallback, observed 2026-08-12T15:32:47.956527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 1438c508-9c1f-4bf2-8518-79a94c2cbf3d · outbound

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

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting Bevdepth: Acquisition of reliable depth for multi-view 3d object detection,

Reference 23

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raw_fallback, observed 2026-08-12T15:32:47.944050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T15:32:47.407902Z digest=sha256:ee746f79a50487bb811f6d34fcb52e04623747afd917eda0d8278701d0d36eb3

Observation 91069a47-1937-4c5c-a039-07e5493ee7dc · outbound

This paper cites Bevfusion: Multi-task multi-sensor fusion with unified bird’s- eye view representation,.

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting Bevfusion: Multi-task multi-sensor fusion with unified bird’s- eye view representation,

Reference 24

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raw_fallback, observed 2026-08-12T15:32:47.933604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T15:32:47.412190Z digest=sha256:15594bb68c9e4596733153a36cb9a7291bf948c6775afe326fce411234a4508c

Observation a7de4b5e-c3c7-4956-8e3f-adebe2f85b2f · outbound

This paper cites Multi-modal hierarchical transformer for occupancy flow field prediction in autonomous driving,.

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting Multi-modal hierarchical transformer for occupancy flow field prediction in autonomous driving,

Reference 25

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raw_fallback, observed 2026-08-12T15:32:47.922546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T15:32:47.416769Z digest=sha256:3bddafb8821db34ea81bfad5c67e3ce001f5abddbe991d5cfaada3ac10a125b5

Observation 9396295c-4231-4b10-a59f-8816df6d87ab · outbound

This paper cites Occupancy flow fields for motion forecasting in autonomous driving,.

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting Occupancy flow fields for motion forecasting in autonomous driving,

Reference 26

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no resolver link, observed 2026-08-12T15:32:47.420875Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:32:47.420875Z digest=sha256:d8bd98e274a501afcae3246fe35b08719a1e280d2e6b968dc6602049ee15e2dc

Observation 309f71fe-fbb8-441d-92b4-342648238963 · outbound

This paper cites Motionnet: Joint perception and motion prediction for autonomous driving based on bird’s eye view maps,.

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting Motionnet: Joint perception and motion prediction for autonomous driving based on bird’s eye view maps,

Reference 27

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raw_fallback, observed 2026-08-12T15:32:47.899887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T15:32:47.425380Z digest=sha256:c8f5ad2ea9a14fb2adea8ee02d56db412d50d60cc0ecb2ce5a6b162db6678f07

Observation 3309eb1d-7308-45fb-b653-53c5beacea6b · outbound

This paper cites Mp3: A unified model to map, perceive, predict and plan,.

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting Mp3: A unified model to map, perceive, predict and plan,

Reference 28

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raw_fallback, observed 2026-08-12T15:32:47.886455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T15:32:47.429804Z digest=sha256:40e10f70897afe35959fea1d8cc7e4565a1e8ffaa6b7f83d0121c3bbff967b4a

Observation 2be51fe1-df04-4eb8-bfa8-ff16d7275de9 · outbound

This paper cites Monet: Motion-based point cloud prediction network,.

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting Monet: Motion-based point cloud prediction network,

Reference 29

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raw_fallback, observed 2026-08-12T15:32:47.872813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T15:32:47.434210Z digest=sha256:facfb653997f40c05b283d2e336ef0287dd8986ba836e60fe766266b0c4638d5

Observation e5e63fe6-adb0-44fd-8092-04ecff60f448 · outbound

This paper cites Pcpnet: An efficient and semantic-enhanced transformer network for point cloud prediction,.

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting Pcpnet: An efficient and semantic-enhanced transformer network for point cloud prediction,

Reference 30

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raw_fallback, observed 2026-08-12T15:32:47.859210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T15:32:47.438514Z digest=sha256:891fa1b70b0c4b13e38ca314fd34e4890ef80dc8bde0143e5a06b1bec7dd2504

Observation 3d4e9868-c702-4fc8-b80d-9d6799dd1021 · outbound

This paper cites ATPPNet: Attention based Temporal Point cloud Prediction Network.

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting ATPPNet: Attention based Temporal Point cloud Prediction Network

Reference 31

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local_arxiv, observed 2026-08-12T15:32:47.590738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T15:32:47.442619Z digest=sha256:c8c99aa964b8fdd96ade249a01a8bd251eb3b789a5e6327b44cf0a882b090ea6

Observation e15a6c4d-681f-469a-bb1b-4547c962e703 · outbound

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

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting Self-supervised point cloud prediction using 3d spatio-temporal convolutional net- works,

Reference 32

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raw_fallback, observed 2026-08-12T15:32:47.732220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T15:32:47.447238Z digest=sha256:7fccbc4e5865284bbf46b40a05491aa61f4f969ec135105b791fda96037c526a

Observation 6b3320ad-339b-43cf-bd53-93e5d60afe05 · outbound

This paper cites PointRNN: Point Recurrent Neural Network for Moving Point Cloud Processing.

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting PointRNN: Point Recurrent Neural Network for Moving Point Cloud Processing

Reference 33

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:32:47.451190Z digest=sha256:061d77fafe198a104cc6b56011be11eb24fae5e092e6fe0e2fea446312f52bf5

Observation aa78ec5e-3509-45c8-9679-c53bdeccfcd4 · outbound

This paper cites OccWorld: Learning a 3D Occupancy World Model for Autonomous Driving.

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting OccWorld: Learning a 3D Occupancy World Model for Autonomous Driving

Reference 34

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:32:47.455530Z digest=sha256:dcc4824d4f8c5d0044be761634426290f4c011f2a89ef35437670360284f3f58

Observation 6277ad01-75d3-4762-83df-c8e66b907c11 · outbound

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

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting OccSora: 4D Occupancy Generation Models as World Simulators for Autonomous Driving

Reference 35

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unresolved
no resolver link, observed 2026-08-12T15:32:47.459743Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:32:47.459743Z digest=sha256:08a0daf178df20be103a6f95085abfd706a74b5afbed96f8a947b907a19e4c4c

Observation 23507d51-4c78-4669-ac56-b92ab23c1637 · outbound

This paper cites Lift, splat, shoot: Encoding images from arbitrary camera rigs by implicitly unprojecting to 3d,.

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting Lift, splat, shoot: Encoding images from arbitrary camera rigs by implicitly unprojecting to 3d,

Reference 36

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verified fuzzy
raw_fallback, observed 2026-08-12T15:32:47.720794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T15:32:47.464171Z digest=sha256:480aae1af3580cdda4761b4ec242f35e959809a1bf92c24a02a78e61bc2a64c5

Observation 3b403d24-ca52-4fd1-8004-595c1856d252 · outbound

This paper cites Deep residual learning for image recognition,.

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting Deep residual learning for image recognition,

Reference 37

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unresolved
no resolver link, observed 2026-08-12T15:32:47.468292Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:32:47.468292Z digest=sha256:3cfd7a205f8d57e92a9947c056abca326915513c47bba3ef48e191f5f61dae17

Observation bcc8d575-b145-44a5-8a69-b359c95c60f7 · outbound

This paper cites Video panoptic seg- mentation,.

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting Video panoptic seg- mentation,

Reference 38

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verified fuzzy
raw_fallback, observed 2026-08-12T15:32:47.700371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T15:32:47.472813Z digest=sha256:210e3314f1baeaf01447a1419f0ee067369a445916c342ec91dc0cd3061e494a

Observation bee717ee-5639-41ce-a2e8-8f457fb5954d · outbound

This paper cites Self-training with noisy student improves imagenet classification,.

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting Self-training with noisy student improves imagenet classification,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:32:47.689419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T15:32:47.477119Z digest=sha256:57b755fd975312dbcd52740cf12c915f3d20894e918030031386c56cfa75dafa

Observation 3604dc8e-7046-46b0-8f12-250a9da37077 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting Adam: A Method for Stochastic Optimization

Reference 40

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unresolved
no resolver link, observed 2026-08-12T15:32:47.482119Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:32:47.482119Z digest=sha256:b280f1356dec58c85a5cfafdf11781b0014c8daa4576b4d9cfa342f63b3b4dfc

Observation b39d30bf-d186-46b1-936a-298a45e79380 · outbound

This paper cites IV of the main text.

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting IV of the main text

Reference 41

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verified fuzzy
raw_fallback, observed 2026-08-12T15:32:47.677676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T15:32:47.486496Z digest=sha256:214e0b23f0889a24117be6c697ca00d66d7e9498a713c852dd2cae4e5d4034d6

Observation 5b78f164-4085-4379-8a3e-8d8addb40139 · outbound

This paper cites As shown in Fig.

Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting As shown in Fig

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:32:47.667313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T15:32:47.491471Z digest=sha256:de5a56192dd31af41678a077ad33e8bc4526d1649e95ec8722221f3ceca4aea9

Pith citing papers

No inbound Pith citation observations are available.