Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-12T12:43:47.580115Z
Paper Citation Record · LEDGER
D$^2$-World: An Efficient World Model through Decoupled Dynamic Flow
As of 12 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2411.17027.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
14 of 14 outbound references displayed
- verified exact1
- verified fuzzy5
- unresolved8
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 0fbc2561-b3bf-4e45-9531-213a7d8d083f · outbound
This paper cites NuPlan: A closed-loop ML-based planning benchmark for autonomous vehicles.
D$^2$-World: An Efficient World Model through Decoupled Dynamic Flow NuPlan: A closed-loop ML-based planning benchmark for autonomous vehicles
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T12:43:47.527748Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 73c44788-e0b9-4e5b-ac85-f87bc7cce703 · outbound
This paper cites Openscene: The largest up-to- date 3d occupancy prediction benchmark in autonomous driving.
D$^2$-World: An Efficient World Model through Decoupled Dynamic Flow Openscene: The largest up-to- date 3d occupancy prediction benchmark in autonomous driving
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:43:47.758624Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 0647f6e3-6b86-4ea2-a139-81e2cc703852 · outbound
This paper cites Faceformer: Speech-driven 3d facial anima- tion with transformers.
D$^2$-World: An Efficient World Model through Decoupled Dynamic Flow Faceformer: Speech-driven 3d facial anima- tion with transformers
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:43:47.746671Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 89ceb0c8-bb7b-4b4b-896f-024f00f34991 · outbound
This paper cites BEVDet: High-performance Multi-camera 3D Object Detection in Bird-Eye-View.
D$^2$-World: An Efficient World Model through Decoupled Dynamic Flow BEVDet: High-performance Multi-camera 3D Object Detection in Bird-Eye-View
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T12:43:47.540651Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 10a0439c-3644-4d33-a942-c2ebaccb56e5 · outbound
This paper cites Point Cloud Forecasting as a Proxy for 4D Occu- pancy Forecasting.
D$^2$-World: An Efficient World Model through Decoupled Dynamic Flow Point Cloud Forecasting as a Proxy for 4D Occu- pancy Forecasting
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:43:47.734159Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 911bbaf4-13cf-4ac7-af26-6deac1c75e77 · outbound
This paper cites BEVStereo: Enhancing Depth Estimation in Multi-view 3D Object Detection with Dynamic Temporal Stereo.
D$^2$-World: An Efficient World Model through Decoupled Dynamic Flow BEVStereo: Enhancing Depth Estimation in Multi-view 3D Object Detection with Dynamic Temporal Stereo
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T12:43:47.548893Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation dc9e9c8a-d129-4f33-ab12-bd238775c671 · outbound
This paper cites Bevformer: Learning bird’s-eye-view representation from multi-camera images via spatiotemporal transformers.
D$^2$-World: An Efficient World Model through Decoupled Dynamic Flow Bevformer: Learning bird’s-eye-view representation from multi-camera images via spatiotemporal transformers
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T12:43:47.553219Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 86cac0a2-6f7c-4b23-87a3-71631b5e4817 · outbound
This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.
D$^2$-World: An Efficient World Model through Decoupled Dynamic Flow Swin transformer: Hierarchical vision transformer using shifted windows
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T12:43:47.557062Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f7440d38-fb28-47b1-b38d-0e3c597da263 · outbound
This paper cites MIMO Is All You Need : A Strong Multi-In-Multi-Out Baseline for Video Prediction.
D$^2$-World: An Efficient World Model through Decoupled Dynamic Flow MIMO Is All You Need : A Strong Multi-In-Multi-Out Baseline for Video Prediction
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T12:43:47.560758Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 558d2171-79be-4c18-ba3b-cb50b82cb75f · outbound
This paper cites Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation.
D$^2$-World: An Efficient World Model through Decoupled Dynamic Flow Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T12:43:47.564794Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 52a886f4-49f2-446a-81ba-9c9890f8b27e · outbound
This paper cites InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutions.
D$^2$-World: An Efficient World Model through Decoupled Dynamic Flow InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutions
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T12:43:47.568564Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 76dedfc7-0f5e-4d29-9604-1aecf4963067 · outbound
This paper cites Sparse single sweep lidar point cloud segmentation via learning contextual shape priors from scene completion.
D$^2$-World: An Efficient World Model through Decoupled Dynamic Flow Sparse single sweep lidar point cloud segmentation via learning contextual shape priors from scene completion
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:43:47.707833Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 9114a0af-e88a-42fa-bdd2-9260f41c9173 · outbound
This paper cites Visual Point Cloud Forecasting enables Scalable Autonomous Driving.
D$^2$-World: An Efficient World Model through Decoupled Dynamic Flow Visual Point Cloud Forecasting enables Scalable Autonomous Driving
Reference 13
- Resolution
- verified exact
- local_arxiv, observed 2026-08-12T12:43:47.616750Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation d1edb3a9-a99e-48a4-bff4-a5d707fdba62 · outbound
This paper cites Radocc: Learning cross-modality occupancy knowledge through ren- dering assisted distillation.
D$^2$-World: An Efficient World Model through Decoupled Dynamic Flow Radocc: Learning cross-modality occupancy knowledge through ren- dering assisted distillation
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:43:47.696409Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Pith citing papers
No inbound Pith citation observations are available.