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Paper Citation Record · LEDGER

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition

As of 17 August 2026, this Paper Citation Record lists 94 of 94 outbound references and 0 inbound Pith citation observations for arXiv:2507.21610.

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

pith.paper-citation-record.v1
2507.21610 v2

Coverage vector

measured 94 of 94 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T12:39:08.199570Z

measured 94 of 94 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

94 of 94 outbound references displayed

  • verified exact8
  • verified fuzzy48
  • unresolved38
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 94154d9a-d712-4637-91f8-794a52d54153 · outbound

This paper cites Ahmed, Siegfried Mercelis, and Ali Anwar.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Ahmed, Siegfried Mercelis, and Ali Anwar

Reference 1

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Observation 14da898d-1c8a-4f4a-8362-48c62948f8a4 · outbound

This paper cites Vehicles-to-everything standardiza- tion, services and enhancements for intelligent transportation systems.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Vehicles-to-everything standardiza- tion, services and enhancements for intelligent transportation systems

Reference 2

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Observation b41e5b3f-a591-4948-9e80-7fff03541e41 · outbound

This paper cites 5g nr- v2x: Toward connected and cooperative autonomous driv- ing.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition 5g nr- v2x: Toward connected and cooperative autonomous driv- ing

Reference 3

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Observation 2a479a14-fd8e-4eb3-8c9a-272262cd30a1 · outbound

This paper cites Malicious drone identification by vi- bration signature measurement: A radar-based approach.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Malicious drone identification by vi- bration signature measurement: A radar-based approach

Reference 4

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source=pdf_text observed=2026-08-06T12:38:58.035420Z digest=sha256:f37b05e02df61c6dd79483c79e86aee2bfa2eab2e877ba4cc8482f3275e94496

Observation f929714b-4c6a-44fc-acb2-46df6cff8929 · outbound

This paper cites nuscenes: A multi- modal dataset for autonomous driving.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition nuscenes: A multi- modal dataset for autonomous driving

Reference 5

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source=pdf_text observed=2026-08-06T12:38:58.174863Z digest=sha256:d9dd3508fe2f657f0b63ae768e31d3ef033649ec08c8bbd46857a79d84673624

Observation 8fddaa09-6f7f-40a7-86d0-2679c360cd73 · outbound

This paper cites NuPlan: A closed-loop ML-based planning benchmark for autonomous vehicles.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition NuPlan: A closed-loop ML-based planning benchmark for autonomous vehicles

Reference 6

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source=pdf_text observed=2026-08-06T12:38:58.313997Z digest=sha256:0b285ec614b2d2828d698b1d4777fcef722f22d3839a79132bd05980e2812b5c

Observation 2877a4e9-b8a1-4c9d-85fc-e4f246aaec5c · outbound

This paper cites Cooperative perception with localization uncertainty: A cubature split covariance intersection framework.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Cooperative perception with localization uncertainty: A cubature split covariance intersection framework

Reference 7

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source=pdf_text observed=2026-08-06T12:38:58.442129Z digest=sha256:8fa2e373434382b1baa5cff973cc0205871911204d24886ae871a874dd39509c

Observation 5e210aba-9128-47d3-b923-f5e76c6e9c7c · outbound

This paper cites Yolov4-5d: An effective and efficient object detector for au- tonomous driving.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Yolov4-5d: An effective and efficient object detector for au- tonomous driving

Reference 8

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source=pdf_text observed=2026-08-06T12:38:58.528773Z digest=sha256:e6ae2cc288b8850770305463d2a1729b3f6d6fa3ce1ac89118b2b153a202b2ad

Observation 9efc55f8-25e1-4b73-91f1-678988315b1c · outbound

This paper cites Bev-v2x: Coop- erative birds-eye-view fusion and grid occupancy prediction via v2x-based data sharing.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Bev-v2x: Coop- erative birds-eye-view fusion and grid occupancy prediction via v2x-based data sharing

Reference 9

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source=pdf_text observed=2026-08-06T12:38:58.630376Z digest=sha256:03777b147508689098f24c8f01f31788297ab488122a5f99c39a5ae1cc02c08a

Observation 380834fa-189c-4a7a-9e51-d93f552de10b · outbound

This paper cites Argoverse: 3d tracking and forecasting with rich maps.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Argoverse: 3d tracking and forecasting with rich maps

Reference 10

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source=pdf_text observed=2026-08-06T12:38:58.775789Z digest=sha256:0a3cb5d86f7ce28e9afd31c81216f784b528fd4dd143f1922edabb3e1606a261

Observation 7f37bfab-39b7-4043-b7ba-6051a2bf6dd2 · outbound

This paper cites Deep neu- ral network based vehicle and pedestrian detection for au- tonomous driving: A survey.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Deep neu- ral network based vehicle and pedestrian detection for au- tonomous driving: A survey

Reference 11

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source=pdf_text observed=2026-08-06T12:38:58.893901Z digest=sha256:67e5c87f8b9ae721512454c6661d84d4f1f96c64d6caaacfe7cb50b914854d1c

Observation ed87f322-8350-4ada-8910-2b5bfe13af1e · outbound

This paper cites End-to-end autonomous driving: Challenges and frontiers.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition End-to-end autonomous driving: Challenges and frontiers

Reference 12

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source=pdf_text observed=2026-08-06T12:38:59.022412Z digest=sha256:aed58fcb394e256d7ca4c37ec4d9cad7c23b4da1b4b5e4c6d2e8db615c269ab3

Observation 95cdd6a6-6ec0-4ca3-95b3-705a1b15a7fa · outbound

This paper cites A fast coordination approach for large-scale drone swarm.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition A fast coordination approach for large-scale drone swarm

Reference 13

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source=pdf_text observed=2026-08-06T12:38:59.137460Z digest=sha256:a625af2986d747aa3b69d1584c2e05af7dccd6aed6353810e4dec72b0fc492f8

Observation f1c2ce55-901a-4a12-b019-ff16fc9ee94b · outbound

This paper cites An Effective Information Theoretic Framework for Channel Pruning.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition An Effective Information Theoretic Framework for Channel Pruning

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:38:59.198501Z digest=sha256:2a4e75cf62a2031e14802b5744d7ed218773d0b2f01c6f55c6a2a23612b83cc6

Observation 919ec57a-a8ca-4bac-8ce1-821445f67cb0 · outbound

This paper cites Transfuser: Imitation with transformer-based sensor fusion for autonomous driv- ing.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Transfuser: Imitation with transformer-based sensor fusion for autonomous driv- ing

Reference 15

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Observation 348c3cf3-8d52-4b3e-928d-82e9167acffb · outbound

This paper cites V2v- llm: Vehicle-to-vehicle cooperative autonomous driving with multi-modal large language models.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition V2v- llm: Vehicle-to-vehicle cooperative autonomous driving with multi-modal large language models

Reference 16

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source=pdf_text observed=2026-08-06T12:38:59.384571Z digest=sha256:27ab75a9884e7e39c899e46085a6f95cb4c730875d4f44605488236f43997e81

Observation 4bfb3d3a-94dd-4492-9b14-43332bf90490 · outbound

This paper cites Drone-assisted cooperative routing scheme for seamless connectivity in v2x communication.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Drone-assisted cooperative routing scheme for seamless connectivity in v2x communication

Reference 17

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Observation f7b4d91c-8e68-4685-8128-b04cdfc177e8 · outbound

This paper cites Wireless access for v2x communi- cations: Research, challenges and opportunities.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Wireless access for v2x communi- cations: Research, challenges and opportunities

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 1397ac8e-997e-4008-8c77-2c49ef9c3ec6 · outbound

This paper cites End-to-end v2x latency modeling and analysis in 5g networks.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition End-to-end v2x latency modeling and analysis in 5g networks

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation a923a14f-fa33-42c5-9d93-b9410754b1c1 · outbound

This paper cites Carla autonomous driving leaderboard, 2024.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Carla autonomous driving leaderboard, 2024

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:38:59.847227Z digest=sha256:ff50ba44f32345c00403b66adb4c89d98794631f746127e9c2dfcc8f7e5c2780

Observation 5494c3fd-dc9b-4860-898d-6af5d93c4417 · outbound

This paper cites CoopReflect: Towards Natural Language Communication for Cooperative Autonomous Driving via Multi-Agent Learning.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition CoopReflect: Towards Natural Language Communication for Cooperative Autonomous Driving via Multi-Agent Learning

Reference 21

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source=pdf_text observed=2026-08-06T12:38:59.937468Z digest=sha256:c951418754df6a9bfe9fa14cbd3cb4e1866894b43815746ce39a597012127f8b

Observation cf629571-09b9-48bc-9e69-0724cf5e9089 · outbound

This paper cites A Vehicle-Infrastructure Multi-layer Cooperative Decision-making Framework.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition A Vehicle-Infrastructure Multi-layer Cooperative Decision-making Framework

Reference 22

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Observation 15df2977-36d0-4bc8-aec4-46907c138709 · outbound

This paper cites Navsim: Data-driven non-reactive autonomous vehicle simulation and benchmarking.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Navsim: Data-driven non-reactive autonomous vehicle simulation and benchmarking

Reference 23

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 2093e04e-3270-4434-bdca-7300b5d1be39 · outbound

This paper cites Carla: An open urban driv- ing simulator.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Carla: An open urban driv- ing simulator

Reference 24

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raw_fallback, observed 2026-08-06T12:39:18.080607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation c3c5322a-9329-4054-b53a-974db4c750b6 · outbound

This paper cites Quest: Query stream for practical cooperative percep- tion.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Quest: Query stream for practical cooperative percep- tion

Reference 25

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 3cfd18e4-b31e-4d38-a26d-3aa191b5afe0 · outbound

This paper cites U2udata: A large-scale cooperative perception dataset for swarm uavs autonomous flight.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition U2udata: A large-scale cooperative perception dataset for swarm uavs autonomous flight

Reference 26

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 3e8b65d6-3f0a-4e81-9a4d-5591a1521c8f · outbound

This paper cites Self- supervised visual odometry based on scene appearance- structure incremental fusion.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Self- supervised visual odometry based on scene appearance- structure incremental fusion

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:00.596547Z digest=sha256:2aac3cb623a7f8442a45d3304d4a768c29919d9a323b71cf7a53779c0248d804

Observation e05be21b-4990-4194-886e-911b00d90a8d · outbound

This paper cites Automated Vehicles Should be Connected with Natural Language.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Automated Vehicles Should be Connected with Natural Language

Reference 28

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source=pdf_text observed=2026-08-06T12:39:00.756335Z digest=sha256:61f2d009fe5a97b0333a8ffbec164336c9f1442bcef7ca0f3f5b6d986b2fc0b7

Observation e1481273-3447-4281-9642-2109eff15659 · outbound

This paper cites Langcoop: Collaborative driving with language.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Langcoop: Collaborative driving with language

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:00.896834Z digest=sha256:9213f841a568029f3ffab1fe133d069460dd5bbc5fb2d6a22802d45cb69ee2fc

Observation 00d2c482-53f2-47e5-b5ee-e1577cbc7486 · outbound

This paper cites AirV2X: Unified Air-Ground Vehicle-to-Everything Collaboration.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition AirV2X: Unified Air-Ground Vehicle-to-Everything Collaboration

Reference 30

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source=pdf_text observed=2026-08-06T12:39:01.024699Z digest=sha256:65bbf64bc5c897a9f2fde4f376cb75dfa2f7351835b60e0b0bbd5ffc9b0100ae

Observation ce804239-a694-4482-a0f5-9784d06eab3f · outbound

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

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition STAMP: Scalable Task And Model-agnostic Collaborative Perception

Reference 31

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source=pdf_text observed=2026-08-06T12:39:01.140801Z digest=sha256:902af2f4e966161bbeaee2720f091703b58d0fd28d842cfa190aed81fb342fc3

Observation 8ac43aab-5adc-4e2e-bcad-c604a99b5e4c · outbound

This paper cites Integrating cybersecurity in v2x: A review of simulation environments.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Integrating cybersecurity in v2x: A review of simulation environments

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:01.241703Z digest=sha256:e4ec9088d6e253cdab2abffc9e28e3819301464e5c82f485f4e35b2f483a1fb3

Observation f257ff64-5ee1-43eb-8dd6-342f63df5dac · outbound

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

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Rcooper: A real-world large-scale dataset for roadside cooperative perception

Reference 33

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raw_fallback, observed 2026-08-06T12:39:17.195045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:01.365243Z digest=sha256:982b2503f855d39a719e869eb53eac9818745ad89b5a197289461cf373b462f3

Observation 496d8f5d-e565-4c7d-ae3c-c9043f5ca5ea · outbound

This paper cites Styledrive: Towards driving-style aware benchmark- ing of end-to-end autonomous driving.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Styledrive: Towards driving-style aware benchmark- ing of end-to-end autonomous driving

Reference 34

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source=pdf_text observed=2026-08-06T12:39:01.476940Z digest=sha256:f07ea87c3874b1947029ebcd2a546fb490a4cf640c57a72b3a05c458bf67df6d

Observation 3f4c6c9a-3976-45bb-897b-aaea25b33eb0 · outbound

This paper cites Agc-drive: A large-scale dataset for real-world aerial-ground collaboration in driving scenarios.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Agc-drive: A large-scale dataset for real-world aerial-ground collaboration in driving scenarios

Reference 35

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no resolver link, observed 2026-08-06T12:39:01.594019Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:39:01.594019Z digest=sha256:be82e876ce002ee3d6c74a40aef9248545ac994903829e6c8fb2fb6e2234a766

Observation ddcb2109-b260-4a03-ab06-f3ffb1822445 · outbound

This paper cites Planning-oriented autonomous driving.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Planning-oriented autonomous driving

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:39:17.056626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:01.718855Z digest=sha256:fd21e1c3a2420a50a940b54ac12967701d72b49954dc948d31bf3d9f33bdd6f9

Observation 1e0871b0-7b23-4154-bb51-6d2e7a0523ed · outbound

This paper cites Gameformer: Game-theoretic modeling and learning of transformer-based interactive prediction and planning for autonomous driving.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Gameformer: Game-theoretic modeling and learning of transformer-based interactive prediction and planning for autonomous driving

Reference 37

Resolution
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raw_fallback, observed 2026-08-06T12:39:16.778732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:01.790271Z digest=sha256:eab351deb9aeb2c1395f420d3991ffd5c8236d31b0b72975103c6f5ee347276b

Observation f9df78b3-1e63-409f-aa8a-8384d23e9065 · outbound

This paper cites Dif- ferentiable integrated motion prediction and planning with learnable cost function for autonomous driving.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Dif- ferentiable integrated motion prediction and planning with learnable cost function for autonomous driving

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:39:16.533068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:01.887388Z digest=sha256:eb20c26ad4903851ea00346a25ccbaa960d6f270d5cf79a0f2bb098be619bc89

Observation 17eea6ad-2d98-482f-866c-fa04e4c5d703 · outbound

This paper cites Rcfl: Redundancy- aware collaborative federated learning in vehicular networks.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Rcfl: Redundancy- aware collaborative federated learning in vehicular networks

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:39:16.357678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:01.968290Z digest=sha256:d4dd1252a82fab9fa5f05a0dec05b61edde723c9a92c14d77b15ab024eeb3ca0

Observation 9b093d5a-bc0e-47a6-a994-0f9ce6f7dd8a · outbound

This paper cites Bench2drive: Towards multi-ability bench- marking of closed-loop end-to-end autonomous driving.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Bench2drive: Towards multi-ability bench- marking of closed-loop end-to-end autonomous driving

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:39:16.188630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:02.069478Z digest=sha256:0777abdd50d9a001fe2ed08e443e953c1c439212ec324a73cf7743dff6eecd3f

Observation 9267d9b9-730b-4e18-aff5-c008ee6d28eb · outbound

This paper cites Vad: Vectorized scene representa- tion for efficient autonomous driving.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Vad: Vectorized scene representa- tion for efficient autonomous driving

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-06T12:39:02.163826Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:39:02.163826Z digest=sha256:be009006d1cec1bdfdb7d03077a7cb256f5209c27400e0845475ea3f723153cf

Observation 6114a5cf-459a-4563-b467-772dcb481c99 · outbound

This paper cites A Survey on Vision-Language-Action Models for Autonomous Driving.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition A Survey on Vision-Language-Action Models for Autonomous Driving

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-06T12:39:02.315303Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:39:02.315303Z digest=sha256:e88e1afb7b2ac76548397bb2325aefe994046e52eb5562ff276069e30b70a191

Observation 2de42e06-6bcd-4e63-b670-9547284b2179 · outbound

This paper cites Dusa: Decoupled unsupervised sim2real adaptation for vehicle-to-everything collaborative perception.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Dusa: Decoupled unsupervised sim2real adaptation for vehicle-to-everything collaborative perception

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:39:16.053209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:02.379314Z digest=sha256:7747e25066113e47b0ce3861d34694aece89236bb127203b18359a9c1ebcc3ef

Observation c1c231ae-b880-42f7-b6ce-b426b026935a · outbound

This paper cites Risk map as middleware: Towards interpretable coop- erative end-to-end autonomous driving for risk-aware plan- ning.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Risk map as middleware: Towards interpretable coop- erative end-to-end autonomous driving for risk-aware plan- ning

Reference 44

Resolution
verified exact
raw_fallback, observed 2026-08-06T12:39:09.763283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:02.476204Z digest=sha256:21ab27e80a35f50bce32dd4e1de13c4f5f13df1e4f72c0394891872f0cb0975b

Observation c0ee71e1-de91-4e6b-b696-b879ea269f4b · outbound

This paper cites V2X-DGW: Domain Generalization for Multi-agent Perception under Adverse Weather Conditions.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition V2X-DGW: Domain Generalization for Multi-agent Perception under Adverse Weather Conditions

Reference 45

Resolution
verified exact
local_arxiv, observed 2026-08-06T12:39:09.549440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:02.559285Z digest=sha256:79bb9acbb24eb66a4c0a9b9b08d686c73464e1786626363dd8840c24d5edcaa9

Observation 7e5b3704-bffe-40c0-9f8f-f0425f7517b8 · outbound

This paper cites Coarse-to-Fine: A Dual-Phase Channel-Adaptive Method for Wireless Image Transmission.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Coarse-to-Fine: A Dual-Phase Channel-Adaptive Method for Wireless Image Transmission

Reference 46

Resolution
verified exact
local_arxiv, observed 2026-08-06T12:39:09.415854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:02.633399Z digest=sha256:13f618ffe02f8d6985e4b98f8a8558f1425e271aa4143eb394405b72a577cdc8

Observation 887a7d94-72aa-4d1a-b673-ba4e9c9c7922 · outbound

This paper cites Efficient collaborative perception with integrated un- certainty estimation via evidence regression.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Efficient collaborative perception with integrated un- certainty estimation via evidence regression

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:39:15.864782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:02.697589Z digest=sha256:e9a297438c8ee948f79a4920107129ad14fd178e20487ef2fec0305f7ec5d972

Observation ceed4cbc-6471-44e1-9320-0b10090a431a · outbound

This paper cites Di-v2x: Learning domain- 10 invariant representation for vehicle-infrastructure collabora- tive 3d object detection.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Di-v2x: Learning domain- 10 invariant representation for vehicle-infrastructure collabora- tive 3d object detection

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:39:15.704374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:02.762758Z digest=sha256:becd2c61291889164fffc9daf60cdfd62989f5dc00e14a648484be3b17dfdd83

Observation 054189e4-87a6-40f3-ad7a-ac0d0f38cf07 · outbound

This paper cites V2x-sim: Multi-agent col- laborative perception dataset and benchmark for autonomous driving.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition V2x-sim: Multi-agent col- laborative perception dataset and benchmark for autonomous driving

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:39:15.522559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:02.869825Z digest=sha256:6d48b4e49e66d3554f803423be7f1435b3794dd6c80e55f35090926f29751b93

Observation 78f466ed-2b8b-44d9-8dc4-1c14460f9212 · outbound

This paper cites A full-scale hierarchical encoder-decoder network with cascading edge-prior for infrared and visible image fusion.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition A full-scale hierarchical encoder-decoder network with cascading edge-prior for infrared and visible image fusion

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:39:15.408496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:02.970397Z digest=sha256:2d73a6d543b6d0a847ceae08ff25744cdc1067887cc1ee3ae4e7c5af179f3464

Observation a6ff47d5-e5cb-4bbc-9c98-4ef13a705906 · outbound

This paper cites V2x-unipool: Unifying multimodal perception and knowl- edge reasoning for autonomous driving.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition V2x-unipool: Unifying multimodal perception and knowl- edge reasoning for autonomous driving

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-06T12:39:03.109673Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:39:03.109673Z digest=sha256:b71ab1ea765fedd49ce54adeaeb3b4cb3b0dd424d1d9de690c37d61fc759a8a1

Observation 549e87ef-94d3-416b-a8b8-474bcd48b2e2 · outbound

This paper cites Class-specific feature selection using fuzzy information- theoretic metrics.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Class-specific feature selection using fuzzy information- theoretic metrics

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:39:15.263475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:03.267125Z digest=sha256:458a66b65b57295547d52cf27088b228c30ac809215270834c470122201465a7

Observation f168be20-f119-4385-a609-49b83b670abe · outbound

This paper cites Collective percep- tion messages: New low complexity fusion and v2x con- nectivity analysis.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Collective percep- tion messages: New low complexity fusion and v2x con- nectivity analysis

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:39:15.141811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:03.360515Z digest=sha256:617911a5d0c77c28d4621c8f339076f8c6a79b7b94a0e18437e1b325a1d9a819

Observation 4be5d4e6-1948-4de0-bddb-b3cd5d68e186 · outbound

This paper cites Vlp: Vision language planning for autonomous driving.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Vlp: Vision language planning for autonomous driving

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:39:15.035086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:03.485058Z digest=sha256:aede74f8b422fdc5710f63ea05502aa70f5b23e8780db37764674fd23dccec10

Observation dbeb14a7-b7bb-4acf-b4d5-d67308f7bf1e · outbound

This paper cites Openscene: 3d scene understanding with open vocabularies.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Openscene: 3d scene understanding with open vocabularies

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-06T12:39:03.625420Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:39:03.625420Z digest=sha256:2730336c03a05e1e1ba7cfa1908130acea0afc99259d93ee18753c873e8de808

Observation a1b4f251-8af0-469d-9509-fb8e8ea1f6cf · outbound

This paper cites Interruption- aware cooperative perception for v2x communication-aided autonomous driving.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Interruption- aware cooperative perception for v2x communication-aided autonomous driving

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:39:14.880139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:03.769610Z digest=sha256:8a553d7e370d91ec7355ba30062b18c494b931e1ecf18d9d6713081027f23b76

Observation f39f906b-faf2-4094-aa46-ef5ceccb0c5d · outbound

This paper cites First mile: An open inno- vation lab for infrastructure-assisted cooperative intelligent transportation systems.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition First mile: An open inno- vation lab for infrastructure-assisted cooperative intelligent transportation systems

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:39:14.697716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:03.906925Z digest=sha256:f2e870f97af31399775c3e2302beba91e2d9ae41f5a5e5d944a1fced8dacc6bf

Observation dce717da-dece-49d0-85aa-5b999dd70ebb · outbound

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

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Col- laborative semantic occupancy prediction with hybrid fea- ture fusion in connected automated vehicles

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:39:14.546316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:04.032696Z digest=sha256:0756dec16a49a5cbceb279f7e8b7c5c28e2069800a310834a3ad77f5f200171c

Observation df902400-38b1-4de3-9f35-928caa67472a · outbound

This paper cites A systematic literature review of vehicular connectivity and v2x communications: Technical aspects and new chal- lenges.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition A systematic literature review of vehicular connectivity and v2x communications: Technical aspects and new chal- lenges

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:39:14.313715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:04.172720Z digest=sha256:45c7fa3625856067991fca3eff217d2230e253c4bd876ce9c216da300ed9733f

Observation 87c0ab78-f090-489b-91ab-10dffd10ca4f · outbound

This paper cites Sae j2735 standard: applying the systems engineering process.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Sae j2735 standard: applying the systems engineering process

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:39:14.150963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:04.310352Z digest=sha256:860a3636202a78cd9f6a9d2af119f881824b52426f8f6c0d3fa42d83c82c49db

Observation a7f9aab9-7b15-4808-a1e2-7360fc283ec9 · outbound

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

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Scalability in perception for autonomous driving: Waymo open dataset

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:39:14.021790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:04.436989Z digest=sha256:a4c8fa567bf4bb40457635bcc762f8c559288e67f0bc8819a89c15ec9f1ea7bf

Observation 14b80b13-00ed-4b50-87aa-58824c2a04e1 · outbound

This paper cites Dy- namic v2x perception from road-to-vehicle vision.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Dy- namic v2x perception from road-to-vehicle vision

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:39:13.879708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:04.578655Z digest=sha256:cd333376f25b9c5e79ab71dd6bf1660bd64caed3261335acfa145dd2ce89d012

Observation 1ad93e3b-f599-4a34-a219-f26fd639e4b1 · outbound

This paper cites A comprehensive overview of the protocols associated with Intelligent Transportation Systems.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition A comprehensive overview of the protocols associated with Intelligent Transportation Systems

Reference 63

Resolution
verified exact
local_arxiv, observed 2026-08-06T12:39:09.129995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:04.750535Z digest=sha256:a7ed31938eb21bb0b59c831e84288573cbb98ae2d238dcc42d170e5246808bac

Observation e173ee88-e4c4-46ed-8114-fd63181be30d · outbound

This paper cites Griffin: Aerial-Ground Cooperative Detection and Tracking Dataset and Benchmark.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Griffin: Aerial-Ground Cooperative Detection and Tracking Dataset and Benchmark

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-06T12:39:04.863133Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:39:04.863133Z digest=sha256:7a1f876fe4f1045fe7cc0a4ea8c03ba27ada15c0bfe3b3a5042ceee7e0645f14

Observation 772da702-3296-473f-97eb-880352e7376b · outbound

This paper cites V2x-dgpe: Addressing domain gaps and pose errors for robust collaborative 3d object detection.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition V2x-dgpe: Addressing domain gaps and pose errors for robust collaborative 3d object detection

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:39:13.653658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:04.973629Z digest=sha256:0787ba7974d3a83da8ef203a3285e78a4ee32df48ce27b03b2b0bd1f32fc3f65

Observation 15ab5f64-82a6-4f79-88f5-1b5ec3433341 · outbound

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

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Driving into the future: Multiview visual forecasting and planning with world model for au- tonomous driving

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-06T12:39:05.091163Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:39:05.091163Z digest=sha256:df6be5fcb26fb3fad39446e50fcad1e80177363c2d8f3039be5d7d5b671643af

Observation ec17bc6e-baa3-40d0-8303-0de833053ace · outbound

This paper cites Toward Realization of Low-Altitude Economy Networks: Core Architecture, Integrated Technologies, and Future Directions.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Toward Realization of Low-Altitude Economy Networks: Core Architecture, Integrated Technologies, and Future Directions

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-06T12:39:05.213461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:39:05.213461Z digest=sha256:95516089ce864ae75bcb436392980aefd1eb32e102bdbc4f0b0f515c3490c516

Observation 098c9caa-5d0e-4179-8561-7f9e3cf88af4 · outbound

This paper cites Generative AI for Autonomous Driving: Frontiers and Opportunities.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Generative AI for Autonomous Driving: Frontiers and Opportunities

Reference 68

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unresolved
no resolver link, observed 2026-08-06T12:39:05.360292Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:39:05.360292Z digest=sha256:ad58981ec646f98cc40ae069ac760a34a504f0c28dd78434891f43aaea9ee9a9

Observation 9ebce9a8-1c1e-4d21-86f7-f9b164dc8198 · outbound

This paper cites CoopDETR: A Unified Cooperative Perception Framework for 3D Detection via Object Query.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition CoopDETR: A Unified Cooperative Perception Framework for 3D Detection via Object Query

Reference 69

Resolution
verified exact
local_arxiv, observed 2026-08-06T12:39:08.939182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:05.501543Z digest=sha256:3e6eb904b35a4809b5015a14e034c7a57ababbc41fb1c3e43403d44a8bf8ba96

Observation 27e0868d-e575-42f9-a59e-68fea7cdbfe4 · outbound

This paper cites Hecofuse: Cross-modal complemen- tary v2x cooperative perception with heterogeneous sensors.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Hecofuse: Cross-modal complemen- tary v2x cooperative perception with heterogeneous sensors

Reference 70

Resolution
verified exact
raw_fallback, observed 2026-08-06T12:39:08.787828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:05.643497Z digest=sha256:7b96be81955c739f745fd75b2e625e71f8ab8519ee423ef57ffb37f0ed899d10

Observation b49ece65-1722-4351-8638-c098268b567a · outbound

This paper cites V2X-LLM: Enhancing V2X Integration and Understanding in Connected Vehicle Corridors.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition V2X-LLM: Enhancing V2X Integration and Understanding in Connected Vehicle Corridors

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-06T12:39:05.748281Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:39:05.748281Z digest=sha256:306b0c6a6f7c1c159989e3e34397c045182761ceb6bce75d07d5804fdb8a7350

Observation 2847d78d-a832-4386-a04f-082ab0114053 · outbound

This paper cites One is plenty: A polymorphic feature interpreter for im- mutable heterogeneous collaborative perception.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition One is plenty: A polymorphic feature interpreter for im- mutable heterogeneous collaborative perception

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:39:13.438559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:05.913924Z digest=sha256:23704f632f11c38c0bbb15f842c01674efc2927283d8149f7f1ceacf8fb3d864

Observation 6d802ea2-5946-4da5-8187-eb92fce2ff8b · outbound

This paper cites V2x-real: a largs-scale dataset for vehicle-to- everything cooperative perception.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition V2x-real: a largs-scale dataset for vehicle-to- everything cooperative perception

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:39:13.293821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:06.086869Z digest=sha256:2c45579a94f96171938aa21e4ad451e68a7649c8ddf41c92a961ec972e13f4e7

Observation f4cd460c-a870-4082-9d09-212ab8e7a0c0 · outbound

This paper cites V2X-ReaLO: An Open Online Framework and Dataset for Cooperative Perception in Reality.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition V2X-ReaLO: An Open Online Framework and Dataset for Cooperative Perception in Reality

Reference 74

Resolution
unresolved
no resolver link, observed 2026-08-06T12:39:06.201331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:39:06.201331Z digest=sha256:5a801158453d325eacfd3493099aed8aa33ba7a8d5d7e505a900145673f86a3f

Observation c4106821-c353-480f-bd94-40a724e87b89 · outbound

This paper cites Autotrust: Benchmark- ing trustworthiness in large vision language models for au- tonomous driving.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Autotrust: Benchmark- ing trustworthiness in large vision language models for au- tonomous driving

Reference 75

Resolution
unresolved
no resolver link, observed 2026-08-06T12:39:06.242483Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:39:06.242483Z digest=sha256:be93f8072775bd5a40164aded5feb4238140b5e1b812cef2cc15a3d41e11faa1

Observation 16ca54a5-ebe7-4d7a-adf5-52dd107fd2fc · outbound

This paper cites Delay-aware cooperative perception with deep reinforce- ment learning in vehicular networks.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Delay-aware cooperative perception with deep reinforce- ment learning in vehicular networks

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:39:13.154831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:06.362291Z digest=sha256:ac74f26a427610ed8056197e93f8286ce4ee702f4c1a35e0a7deb0893321b7c6

Observation fb87abb5-dea3-408c-b060-b66ffc3fc613 · outbound

This paper cites V2x-vit: Vehicle-to-everything cooperative perception with vision transformer.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition V2x-vit: Vehicle-to-everything cooperative perception with vision transformer

Reference 77

Resolution
unresolved
no resolver link, observed 2026-08-06T12:39:06.502123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:39:06.502123Z digest=sha256:064f1cab8a95a7d34ac82f3e04dc441381402778f38d6f8bee45e6c25f2921d5

Observation 5b03e4d3-bf6a-4eba-aace-73e2e3a07bd1 · outbound

This paper cites V2v4real: A real-world large-scale dataset for vehicle-to-vehicle cooperative perception.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition V2v4real: A real-world large-scale dataset for vehicle-to-vehicle cooperative perception

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:39:12.889245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:06.608657Z digest=sha256:9be45e0f22b481f9fad31f5c942bf2ae908ec106df9f19bdc125a534b074ff51

Observation f444060d-559a-4260-bd6e-1ba111215d75 · outbound

This paper cites V2x-vitv2: Improved vision transformers for vehicle-to-everything cooperative perception.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition V2x-vitv2: Improved vision transformers for vehicle-to-everything cooperative perception

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:39:12.715836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:06.700102Z digest=sha256:45a17f3a8fbd1532066b99dcc89cbc01064d1d8a0a439d77033bbb8eb0bd58d8

Observation 1e1f1532-0ce1-4e0d-9d98-b6c98bd2a3d4 · outbound

This paper cites Cooperative sensing and heterogeneous information fusion in vcps: A multi-agent deep reinforce- ment learning approach.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Cooperative sensing and heterogeneous information fusion in vcps: A multi-agent deep reinforce- ment learning approach

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:39:12.495715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:06.790745Z digest=sha256:df49145f37cdfbd2f2fc7144864610fafd08d35974ce52a3caf8fe356b33009f

Observation e3a0cb48-e3a1-49b0-aac8-3dc94b95ca8f · outbound

This paper cites Au- tonomous driving under v2x environment: state-of-the-art survey and challenges.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Au- tonomous driving under v2x environment: state-of-the-art survey and challenges

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:39:12.286269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:06.848966Z digest=sha256:13265cd47c9bd5a6724379c82ff357a07000703738401ae4f332bf4cc818c653

Observation f4413b5e-2011-4e05-abb1-67e2421cfc47 · outbound

This paper cites V2iviewer: Towards efficient collaborative perception via point cloud data fusion and vehicle-to-infrastructure communications.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition V2iviewer: Towards efficient collaborative perception via point cloud data fusion and vehicle-to-infrastructure communications

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:39:12.022981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:06.948698Z digest=sha256:bb36a65aad5b32864c5a9fa92f2ee7217b91e247a79cfaad5e57c20fae31f789

Observation 961c3e8f-a32a-4c77-ab2c-82d91b8744f9 · outbound

This paper cites V2X-VLM: End-to-End V2X Cooperative Autonomous Driving Through Large Vision-Language Models.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition V2X-VLM: End-to-End V2X Cooperative Autonomous Driving Through Large Vision-Language Models

Reference 83

Resolution
unresolved
no resolver link, observed 2026-08-06T12:39:07.063571Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:39:07.063571Z digest=sha256:d0e172a72102159cdf8a5ebf328abf9e3c7116a5c958eaa52c7a6e2a376ff292

Observation 2980c87b-5103-4ed5-a1bf-aa8b98bbef2f · outbound

This paper cites Dair-v2x: A large-scale dataset for vehicle- infrastructure cooperative 3d object detection.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Dair-v2x: A large-scale dataset for vehicle- infrastructure cooperative 3d object detection

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:39:11.785565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:07.146986Z digest=sha256:a5ddd0db98ef6edb2480ebcd0e03f1606e5b5d8dba872fdd560c2387cfbcaa54

Observation 90068da8-a407-4130-931d-4577217dd578 · outbound

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

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Flow-based feature fusion for vehicle- infrastructure cooperative 3d object detection

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:39:11.633212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:07.245482Z digest=sha256:c73c99e82d77d818adccbd3bbdf590ce8bff0541576c536dce38c8d4871d7e33

Observation c1616a9d-53b8-4b1f-a4af-6c64a2136f30 · outbound

This paper cites V2x-seq: A large-scale sequential dataset for vehicle-infrastructure cooperative perception and forecast- ing.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition V2x-seq: A large-scale sequential dataset for vehicle-infrastructure cooperative perception and forecast- ing

Reference 86

Resolution
unresolved
no resolver link, observed 2026-08-06T12:39:07.349328Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:39:07.349328Z digest=sha256:625003d191fabd198f83507533f9a7705fd6722bf985f37b7b7d18b2f0911963

Observation 67baa52e-f6d4-4b46-8d19-5863a68857b8 · outbound

This paper cites End-to-end autonomous driving through v2x cooperation.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition End-to-end autonomous driving through v2x cooperation

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:39:11.428373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:07.538224Z digest=sha256:9a1db830b1284780c6a49291ebd9f84d3216ecd13dd9afabf5acce5690978a65

Observation 2d746616-b053-44b3-9492-d2a07eec9c5d · outbound

This paper cites Vehicle- to-everything (v2x) in the autonomous vehicles domain–a technical review of communication, sensor, and ai technolo- gies for road user safety.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Vehicle- to-everything (v2x) in the autonomous vehicles domain–a technical review of communication, sensor, and ai technolo- gies for road user safety

Reference 88

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:39:11.251827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:07.633329Z digest=sha256:5b7a3bc8f8dc99b907e327a558337686aca07cde1130f01f424fe533c27c812f

Observation 53ea4f91-4b6a-4627-8718-967e8e55cf31 · outbound

This paper cites Heterogeneous multi- scale cooperative perception for connected autonomous ve- hicles via v2x interaction.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Heterogeneous multi- scale cooperative perception for connected autonomous ve- hicles via v2x interaction

Reference 89

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:39:10.998705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:07.713988Z digest=sha256:31400ff4685b3ac5120ec4dad37c5833b1499b5158bdec081673e5eff4708a29

Observation 8cd9e3a6-dd5f-4615-b04f-40df7e6678b3 · outbound

This paper cites Remote driving of road vehicles: A survey of driving feed- back, latency, support control, and real applications.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Remote driving of road vehicles: A survey of driving feed- back, latency, support control, and real applications

Reference 90

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:39:10.815513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:07.805735Z digest=sha256:fbe109ccc056acc1a611f18a099bed04cc71115e3e8cbe0e0912c16e877ea3c2

Observation 46f57b66-3913-44c7-a6ea-ed94ca1ab345 · outbound

This paper cites CooPre: Cooperative Pretraining for V2X Cooperative Perception.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition CooPre: Cooperative Pretraining for V2X Cooperative Perception

Reference 91

Resolution
unresolved
no resolver link, observed 2026-08-06T12:39:07.879426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:39:07.879426Z digest=sha256:87be6e7fe61ce21f6d854b3a408ade97f4fc00a17f6f480f066e3c63ff245b40

Observation 0067c635-e935-47cb-973d-2d10db8fe1f4 · outbound

This paper cites Leveraging temporal con- texts to enhance vehicle-infrastructure cooperative percep- tion.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Leveraging temporal con- texts to enhance vehicle-infrastructure cooperative percep- tion

Reference 92

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:39:10.665984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:07.986639Z digest=sha256:2880ae54ad6cfc8c645a04d611f16d18b88b1293766020e048ed27c3bbd5b234

Observation 5333bc41-8e11-4147-8970-f27d89a900dc · outbound

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

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition CoopTrack: Exploring End-to-End Learning for Efficient Cooperative Sequential Perception

Reference 93

Resolution
verified exact
local_arxiv, observed 2026-08-06T12:39:08.367707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:08.098102Z digest=sha256:38807cc76ee4c53ca758dff660c4b3e3ea05b2496997d0fe939131da2bcbb8ab

Observation eec8c793-bb38-47df-822e-72933ca13712 · outbound

This paper cites Tum- traf v2x cooperative perception dataset.

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition Tum- traf v2x cooperative perception dataset

Reference 94

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:39:10.515398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T12:39:08.199570Z digest=sha256:4aeae54fb21c0d53957a5f62e5d2a2b26a037f357203c011487d27866782a6fc

Pith citing papers

No inbound Pith citation observations are available.