Paper Citation Record · LEDGER

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction

As of 21 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 13 inbound Pith citation observations for arXiv:2412.01812.

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

pith.paper-citation-record.v1
2412.01812 v3

Coverage vector

measured 58 of 58 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T00:59:47.972309Z

measured 71 of 71 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:28:47.760039Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T03:00:48.018147Z

Reference resolution

58 of 58 outbound references displayed

verified exact1
verified fuzzy42
unresolved15
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b2e6b150-3667-48b2-99b2-4bbde885a9b0 · outbound

This paper cites an unresolved cited work.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-12T00:59:49.397545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5cb7d321-7e46-497e-b55e-9ba730ef0d7c · outbound

This paper cites Implicit occupancy flow fields for perception and prediction in self-driving.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction Implicit occupancy flow fields for perception and prediction in self-driving

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:49.374928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f70b8cf4-e391-4256-87dd-181f36aeadb1 · outbound

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

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction Uno: Unsupervised occupancy fields for perception and forecasting

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:49.353717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 03a8d482-e239-4c94-9d03-b7543d40041f · outbound

This paper cites An overview of vehicular communications.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction An overview of vehicular communications

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:49.333415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6247000b-6088-46a5-8683-69aad3b9526d · outbound

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

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction Lang, Sourabh V ora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Gi- ancarlo Baldan, and Oscar Beijbom

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:49.312709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation fa8f9a3b-2db4-4165-b124-8b8870bef576 · outbound

This paper cites F-cooper: Feature based cooperative perception for autonomous vehicle edge computing system using 3d point clouds.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction F-cooper: Feature based cooperative perception for autonomous vehicle edge computing system using 3d point clouds

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:49.290228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a1d6129e-7fbd-4aee-a6a9-52016a64e085 · outbound

This paper cites Roadrunner: Towards automatic data extraction from large web sites.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction Roadrunner: Towards automatic data extraction from large web sites

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:49.270970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5c3fe121-a551-4a09-9754-8811a1c6ad5d · outbound

This paper cites an unresolved cited work.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-08-12T00:59:49.245322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f2b2cd8f-c7e2-419e-87f1-5a347b9b35e9 · outbound

This paper cites Large scale interactive motion forecasting for autonomous driving: The waymo open mo- tion dataset.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction Large scale interactive motion forecasting for autonomous driving: The waymo open mo- tion dataset

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:49.219869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 405e0415-48e8-4b59-9228-41d8372e7259 · outbound

This paper cites STAMP: Scalable Task And Model-agnostic Collaborative Perception.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction STAMP: Scalable Task And Model-agnostic Collaborative Perception

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-12T00:59:47.364260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5016e054-d41f-49ac-bfab-a832b2057ada · outbound

This paper cites Densetnt: End-to-end trajectory prediction from dense goal sets.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction Densetnt: End-to-end trajectory prediction from dense goal sets

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:49.196741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 19b3a9cb-1f02-4777-9a82-1a808d8b6042 · outbound

This paper cites ViP3D: End-to-End Visual Trajectory Prediction via 3D Agent Queries.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction ViP3D: End-to-End Visual Trajectory Prediction via 3D Agent Queries

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:49.176569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4ef14722-f91b-4d99-8566-f2e5cbed7333 · outbound

This paper cites Foundation intelligence for smart infras- tructure services in transportation 5.0.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction Foundation intelligence for smart infras- tructure services in transportation 5.0

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:49.157142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ab517a43-c78e-408e-840b-e0e60fea1dab · outbound

This paper cites Rcooper: A real-world large-scale dataset for roadside cooperative perception.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction Rcooper: A real-world large-scale dataset for roadside cooperative perception

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:49.135975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0fff4b1e-af68-438a-841b-e3e0e1b3e93b · outbound

This paper cites Where2comm: Communication-efficient collaborative perception via spatial confidence maps.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction Where2comm: Communication-efficient collaborative perception via spatial confidence maps

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:49.112388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d97dfcc2-32f5-4550-b976-79eee310f7ab · outbound

This paper cites Planning-oriented Autonomous Driving.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction Planning-oriented Autonomous Driving

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-12T00:59:47.396606Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e254d8dc-2932-46a4-be2c-eef6b51d5837 · outbound

This paper cites V2X-R: Cooperative LiDAR-4D Radar Fusion with Denoising Diffusion for 3D Object Detection.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction V2X-R: Cooperative LiDAR-4D Radar Fusion with Denoising Diffusion for 3D Object Detection

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-12T00:59:47.443153Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 959136fa-378a-4e63-8213-d6075bc1cd87 · outbound

This paper cites A Survey on Trajectory-Prediction Methods for Autonomous Driving.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction A Survey on Trajectory-Prediction Methods for Autonomous Driving

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:49.091005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a1d2c803-e3c3-4d36-aaea-69a1edcabf8e · outbound

This paper cites To- wards autonomous vehicles: a survey on cooperative vehicle- infrastructure system.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction To- wards autonomous vehicles: a survey on cooperative vehicle- infrastructure system

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:49.062497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e5a28191-8e6d-47e4-8bb3-5e1f4089956d · outbound

This paper cites HDGT: Heterogeneous Driving Graph Trans- former for Multi-Agent Trajectory Prediction Via Scene En- coding.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction HDGT: Heterogeneous Driving Graph Trans- former for Multi-Agent Trajectory Prediction Via Scene En- coding

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:49.041871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation fdee9f4a-6dfc-4b43-8801-13900cdb5c8b · outbound

This paper cites Vad: Vectorized scene representation for ef- ficient autonomous driving.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction Vad: Vectorized scene representation for ef- ficient autonomous driving

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:49.018546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7e673115-a0ad-4aa9-bfa7-6d91c9941320 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction Adam: A Method for Stochastic Optimization

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-12T00:59:47.544926Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 895e39d8-9918-40b5-91d4-bdba9099a3ab · outbound

This paper cites The highD Dataset: A Drone Dataset of Naturalis- tic Vehicle Trajectories on German Highways for Validation 9 of Highly Automated Driving Systems.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction The highD Dataset: A Drone Dataset of Naturalis- tic Vehicle Trajectories on German Highways for Validation 9 of Highly Automated Driving Systems

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:48.992440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1316dbb3-fb35-4d26-8da4-7115c2adc313 · outbound

This paper cites Lang, Sourabh V ora, Holger Caesar, Lubing Zhou, Jiong Yang, and Oscar Beijbom.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction Lang, Sourabh V ora, Holger Caesar, Lubing Zhou, Jiong Yang, and Oscar Beijbom

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:48.971587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 40913465-20fe-4330-9de6-3aaaad0fbef9 · outbound

This paper cites Sustech points: A portable 3d point cloud interactive annotation platform system.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction Sustech points: A portable 3d point cloud interactive annotation platform system

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:48.949277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d47e24e7-ebb4-470e-a9d3-7cea8b465243 · outbound

This paper cites Multi-robot scene completion: Towards task-agnostic collaborative perception.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction Multi-robot scene completion: Towards task-agnostic collaborative perception

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:48.924202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b9a550ac-1887-4dc6-88d6-6dd69d0101b5 · outbound

This paper cites Learning distilled collaboration graph for multi-agent perception.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction Learning distilled collaboration graph for multi-agent perception

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:48.900601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 443fb168-e1de-4719-ac11-3f9020290d1f · outbound

This paper cites V2X-Sim: Multi-Agent Collab- orative Perception Dataset and Benchmark for Autonomous Driving.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction V2X-Sim: Multi-Agent Collab- orative Perception Dataset and Benchmark for Autonomous Driving

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:48.878436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f9904b87-3772-4855-ab4c-b84d38769f98 · outbound

This paper cites BEVFormer: Learning Bird’s-Eye-View Representation from Multi-camera Images via Spatiotemporal Transformers.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction BEVFormer: Learning Bird’s-Eye-View Representation from Multi-camera Images via Spatiotemporal Transformers

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:48.859338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7723dadd-cbd3-44cc-a677-e834b5acad26 · outbound

This paper cites PnPNet: End-to-End Perception and Prediction With Tracking in the Loop.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction PnPNet: End-to-End Perception and Prediction With Tracking in the Loop

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:48.837895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 30cfe1ae-2663-411e-870c-272e0a503184 · outbound

This paper cites Focal loss for dense object detection.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction Focal loss for dense object detection

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:48.817479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation cd9c8746-cd48-4d66-8f94-8715745ee8c5 · outbound

This paper cites An Extensible Framework for Open Heterogeneous Collaborative Perception.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction An Extensible Framework for Open Heterogeneous Collaborative Perception

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-12T00:59:47.597569Z

Source-reported events for the cited work

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Observation 8d076e28-ba93-4871-b05b-421ee519d523 · outbound

This paper cites Fast and Furious: Real Time End-to-End 3D Detection, Tracking and Motion Forecasting With a Single Convolutional Net.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction Fast and Furious: Real Time End-to-End 3D Detection, Tracking and Motion Forecasting With a Single Convolutional Net

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:48.795340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9ef610d4-0581-453f-bb71-25d763e0e6d2 · outbound

This paper cites Learning Cooperative Trajectory Representations for Motion Forecasting.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction Learning Cooperative Trajectory Representations for Motion Forecasting

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-12T00:59:47.670634Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c4a1a0c-cbec-4a53-b612-ad194f4ba7d1 · outbound

This paper cites Are socially-aware trajectory prediction models really socially-aware? Transportation Re- search Part C: Emerging Technologies, 141:103705, 2022.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction Are socially-aware trajectory prediction models really socially-aware? Transportation Re- search Part C: Emerging Technologies, 141:103705, 2022

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:48.775310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8d8299a2-3487-4f3f-94a9-e7966aec09ee · outbound

This paper cites Trajectron++: Dynamically-feasible trajec- tory forecasting with heterogeneous data.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction Trajectron++: Dynamically-feasible trajec- tory forecasting with heterogeneous data

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:48.753635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 571d44fa-d8ba-4fdb-b24d-616b2c7de3d4 · outbound

This paper cites MTR++: Multi-Agent Motion Prediction with Symmetric Scene Modeling and Guided Intention Querying.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction MTR++: Multi-Agent Motion Prediction with Symmetric Scene Modeling and Guided Intention Querying

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-12T00:59:47.740694Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 39f8598f-1720-4e85-9be7-01bf8cf7b6a2 · outbound

This paper cites Col- laborative semantic occupancy prediction with hybrid feature fusion in connected automated vehicles.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction Col- laborative semantic occupancy prediction with hybrid feature fusion in connected automated vehicles

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:48.733388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 808ef5b6-5f43-4ea0-980c-e41241ae530c · outbound

This paper cites Scalability in Perception for Autonomous Driving: Waymo Open Dataset.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction Scalability in Perception for Autonomous Driving: Waymo Open Dataset

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:48.706209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b93ce3d6-369d-431e-bd94-51c3d2a8e3b1 · outbound

This paper cites V2VNet: Vehicle-to-Vehicle Communication for Joint Perception and Prediction.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction V2VNet: Vehicle-to-Vehicle Communication for Joint Perception and Prediction

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-12T00:59:47.758288Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1fc5ab8b-7998-43e1-979b-7736713bf58b · outbound

This paper cites CMP: Cooperative Motion Prediction with Multi-Agent Communication.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction CMP: Cooperative Motion Prediction with Multi-Agent Communication

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-12T00:59:47.763509Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e1d0822-05e8-4369-9783-fc778224ca50 · outbound

This paper cites Asynchrony-robust collaborative perception via bird’s eye view flow.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction Asynchrony-robust collaborative perception via bird’s eye view flow

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:48.682174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b75b0b3b-edeb-433a-9828-f03d3ef4684a · outbound

This paper cites HM-ViT: Hetero-modal Vehicle-to-Vehicle Cooperative perception with vision transformer.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction HM-ViT: Hetero-modal Vehicle-to-Vehicle Cooperative perception with vision transformer

Reference 43

Resolution: verified exact; local_arxiv, observed 2026-08-12T00:59:48.227909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c515cc3c-ffc8-42f9-83ce-1f3d81e2acfc · outbound

This paper cites V2X-Real: a Large-Scale Dataset for Vehicle-to-Everything Cooperative Perception.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction V2X-Real: a Large-Scale Dataset for Vehicle-to-Everything Cooperative Perception

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-12T00:59:47.779450Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd6be088-757d-42bd-9234-92070926913d · outbound

This paper cites V2X-ViT: Vehicle-to-Everything Cooperative Perception with Vision Transformer.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction V2X-ViT: Vehicle-to-Everything Cooperative Perception with Vision Transformer

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:48.658766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7b8b0c39-db6b-4ffb-87d8-d56993374434 · outbound

This paper cites OPV2V: An Open Benchmark Dataset and Fusion Pipeline for Perception with Vehicle-to-Vehicle Communi- cation.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction OPV2V: An Open Benchmark Dataset and Fusion Pipeline for Perception with Vehicle-to-Vehicle Communi- cation

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:48.638922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 31e4f97c-2763-491e-a48e-b5d137af6e3e · outbound

This paper cites V2V4Real: A Real-World Large-Scale Dataset for Vehicle-to-Vehicle Cooperative Perception.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction V2V4Real: A Real-World Large-Scale Dataset for Vehicle-to-Vehicle Cooperative Perception

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:48.616115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0feb6c0c-a2aa-434a-a0db-6d7afadd3e15 · outbound

This paper cites Spatio-Temporal Domain Awareness for Multi-Agent Col- laborative Perception.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction Spatio-Temporal Domain Awareness for Multi-Agent Col- laborative Perception

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:48.591549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c3b8cb0e-00d8-4963-9ebb-01ba7f06518d · outbound

This paper cites DAIR-V2X: A Large-Scale Dataset for Vehicle-Infrastructure Cooperative 3D Object Detection.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction DAIR-V2X: A Large-Scale Dataset for Vehicle-Infrastructure Cooperative 3D Object Detection

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:48.572387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation fa3c47e4-34d4-44b4-a2f4-20bad1e53962 · outbound

This paper cites V2X-Seq: A Large-Scale Sequential Dataset for Vehicle- Infrastructure Cooperative Perception and Forecasting.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction V2X-Seq: A Large-Scale Sequential Dataset for Vehicle- Infrastructure Cooperative Perception and Forecasting

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:48.553485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a0a40b0d-b11c-44b1-9588-008cd06d53ae · outbound

This paper cites Flow-based feature fusion for vehicle- infrastructure cooperative 3d object detection.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction Flow-based feature fusion for vehicle- infrastructure cooperative 3d object detection

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:48.532893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation da9bd01d-9659-4e25-ab1c-6133726f7138 · outbound

This paper cites End-to-End Autonomous Driving through V2X Cooperation.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction End-to-End Autonomous Driving through V2X Cooperation

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-12T00:59:47.946829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65db2cb3-f239-475b-9d4d-d52e3f9c8f9d · outbound

This paper cites Co-mtp: A cooperative tra- jectory prediction framework with multi-temporal fusion for autonomous driving.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction Co-mtp: A cooperative tra- jectory prediction framework with multi-temporal fusion for autonomous driving

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-12T00:59:47.952025Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c70db43f-64e4-42db-a5a8-08e2aad05225 · outbound

This paper cites Zhao, Hao Xiang, Chenfeng Xu, Xin Xia, Bolei Zhou, and Jiaqi Ma.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction Zhao, Hao Xiang, Chenfeng Xu, Xin Xia, Bolei Zhou, and Jiaqi Ma

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:48.513895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e07feaa4-d80a-49db-82e0-715f98dcb364 · outbound

This paper cites Cooperfuse: A real-time cooperative perception fusion framework.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction Cooperfuse: A real-time cooperative perception fusion framework

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:48.492505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f9874f4a-7521-4b62-870d-7ce7c2e13898 · outbound

This paper cites A comprehensive study of speed prediction in transportation system: From vehicle to traffic.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction A comprehensive study of speed prediction in transportation system: From vehicle to traffic

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:48.474188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7f2e86e7-b9e5-44b1-9eca-1c2c927eb0d4 · outbound

This paper cites Tum- traf v2x cooperative perception dataset.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction Tum- traf v2x cooperative perception dataset

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:59:48.453941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c3d4a0e6-a785-4b1b-a677-3dbc838febc0 · outbound

This paper cites V2X-Seq: A Large-Scale Sequential Dataset for Vehicle-Infrastructure Cooperative Perception and Forecasting.

V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction V2X-Seq: A Large-Scale Sequential Dataset for Vehicle-Infrastructure Cooperative Perception and Forecasting

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-12T00:59:47.936071Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 3e4e21ca-7ee1-46f3-8389-490316697ee6 · inbound

Knowledge-Informed Multi-Agent Trajectory Prediction at Signalized Intersections for Infrastructure-to-Everything cites this paper.

Knowledge-Informed Multi-Agent Trajectory Prediction at Signalized Intersections for Infrastructure-to-Everything V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T15:59:46.670585Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d2d74a0-69bc-4aa1-824c-8a0019b59475 · inbound

Collaborative Perception Datasets for Autonomous Driving: A Review cites this paper.

Collaborative Perception Datasets for Autonomous Driving: A Review V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction

Reference 92

Resolution: unresolved; no resolver link, observed 2026-08-16T12:28:47.760039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 45385a2f-9105-403e-8854-008fb58f5974 · inbound

AutoVLA: A Vision-Language-Action Model for End-to-End Autonomous Driving with Adaptive Reasoning and Reinforcement Fine-Tuning cites this paper.

AutoVLA: A Vision-Language-Action Model for End-to-End Autonomous Driving with Adaptive Reasoning and Reinforcement Fine-Tuning V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction

Reference 60

Resolution: verified exact; arxiv_id, observed 2026-05-14T21:46:44.041463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation fbb5cd82-3d4c-42ec-8bca-d06758e8eb4d · inbound

CooperRisk: A Driving Risk Quantification Pipeline with Multi-Agent Cooperative Perception and Prediction cites this paper.

CooperRisk: A Driving Risk Quantification Pipeline with Multi-Agent Cooperative Perception and Prediction V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-15T19:36:24.279304Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5644f759-7981-4885-9229-2d1ad6b7c88f · inbound

CoopTrack: Exploring End-to-End Learning for Efficient Cooperative Sequential Perception cites this paper.

CoopTrack: Exploring End-to-End Learning for Efficient Cooperative Sequential Perception V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-15T18:00:21.111587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 19fb31bb-5a9c-400e-98b1-d48b1d33612f · inbound

CDA-SimBoost: A Unified Framework Bridging Real Data and Simulation for Infrastructure-Based CDA Systems cites this paper.

CDA-SimBoost: A Unified Framework Bridging Real Data and Simulation for Infrastructure-Based CDA Systems V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-06T14:10:35.463603Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d59ac15-1781-428d-a033-b436f8274c40 · inbound

Progressive Bird's Eye View Perception for Safety-Critical Autonomous Driving: A Comprehensive Survey cites this paper.

Progressive Bird's Eye View Perception for Safety-Critical Autonomous Driving: A Comprehensive Survey V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction

Reference 286

Resolution: unresolved; no resolver link, observed 2026-08-05T22:06:55.831008Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88741610-8afd-4c5e-8040-592c71d8ca22 · inbound

QuantV2X: A Fully Quantized Multi-Agent System for Cooperative Perception cites this paper.

QuantV2X: A Fully Quantized Multi-Agent System for Cooperative Perception V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-05T10:50:17.035607Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 475a20fc-a0a8-4c6f-8f9b-68974df12f03 · inbound

All You Need for Object Detection: From Pixels, Points, and Prompts to Next-Gen Fusion and Multimodal LLMs/VLMs in Autonomous Vehicles cites this paper.

All You Need for Object Detection: From Pixels, Points, and Prompts to Next-Gen Fusion and Multimodal LLMs/VLMs in Autonomous Vehicles V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction

Reference 116

Resolution: verified exact; arxiv_id, observed 2026-05-18T03:00:48.020920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d7b3cdb5-44ce-4b4f-aba3-d96aa258109b · inbound

End-to-End 3-D Spatiotemporal Perception with Multimodal Fusion and V2X Collaboration cites this paper.

End-to-End 3-D Spatiotemporal Perception with Multimodal Fusion and V2X Collaboration V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-03T14:05:26.032618Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e812c12a-e386-493e-ae40-b47bc47c2131 · inbound

SpanVLA: Efficient Action Bridging and Learning from Negative-Recovery Samples for Vision-Language-Action Model cites this paper.

SpanVLA: Efficient Action Bridging and Learning from Negative-Recovery Samples for Vision-Language-Action Model V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction

Reference 83

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T12:56:11.390402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5e91d1a8-badd-4fa6-b1c1-4a4877b32547 · inbound

CMU-Drive and V2V-VLA: Cooperative Multi-agent Unified Driving with Reasoning Benchmark and Vehicle-to-Vehicle Vision-Language-Action Models cites this paper.

CMU-Drive and V2V-VLA: Cooperative Multi-agent Unified Driving with Reasoning Benchmark and Vehicle-to-Vehicle Vision-Language-Action Models V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-11T00:32:33.372053Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3dbc6d82-8fcc-40f2-8c28-fb7926a7dc6d · inbound

Towards Collaborative Joint Perception and Prediction: Framework, Baseline Evaluation, and Deployment Perspectives cites this paper.

Towards Collaborative Joint Perception and Prediction: Framework, Baseline Evaluation, and Deployment Perspectives V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-11T15:28:59.299873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.