Paper Citation Record · LEDGER

An End-to-End Collaborative Learning Approach for Connected Autonomous Vehicles in Occluded Scenarios

As of 15 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2412.08562.

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

pith.paper-citation-record.v1
2412.08562 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T17:48:04.047227Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+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

34 of 34 outbound references displayed

verified exact7
verified fuzzy17
unresolved10
parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 643d5cc4-53b7-4082-881a-d1d7f05088b7 · outbound

This paper cites Risk-Aware High-level Decisions for Automated Driving at Occluded Intersections with Reinforcement Learning.

An End-to-End Collaborative Learning Approach for Connected Autonomous Vehicles in Occluded Scenarios Risk-Aware High-level Decisions for Automated Driving at Occluded Intersections with Reinforcement Learning

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-08-11T17:48:04.286148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0b2073e1-463e-4568-918f-34c7920c1868 · outbound

This paper cites Navigating Occluded Intersections with Autonomous Vehicles using Deep Reinforcement Learning.

An End-to-End Collaborative Learning Approach for Connected Autonomous Vehicles in Occluded Scenarios Navigating Occluded Intersections with Autonomous Vehicles using Deep Reinforcement Learning

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-11T17:48:03.920884Z

Source-reported events for the cited work

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Observation 38fa58a1-52ec-4ced-8cd1-56fb0645001f · outbound

This paper cites Broadcasting in V ANET,.

An End-to-End Collaborative Learning Approach for Connected Autonomous Vehicles in Occluded Scenarios Broadcasting in V ANET,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:04.507168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ff84ed8f-1e03-46a7-bf5a-ace0b761c82e · outbound

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

An End-to-End Collaborative Learning Approach for Connected Autonomous Vehicles in Occluded Scenarios OPV2V: An Open Benchmark Dataset and Fusion Pipeline for Perception with Vehicle-to-Vehicle Communication

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-08-11T17:48:04.258521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b61a5430-d845-484c-b5f2-0ca1a23ccfeb · outbound

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

An End-to-End Collaborative Learning Approach for Connected Autonomous Vehicles in Occluded Scenarios V2X-ViT: Vehicle-to-Everything Cooperative Perception with Vision Transformer

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-11T17:48:03.934094Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8b2c02eb-de55-412c-a3bc-c5112782f0d9 · outbound

This paper cites COOPERNAUT: End-to-End Driving with Cooperative Perception for Networked Vehicles.

An End-to-End Collaborative Learning Approach for Connected Autonomous Vehicles in Occluded Scenarios COOPERNAUT: End-to-End Driving with Cooperative Perception for Networked Vehicles

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T17:48:03.938310Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2fc5c16c-bac3-46e5-a1d9-729e6ddab7af · outbound

This paper cites Exploring the Limitations of Behavior Cloning for Autonomous Driving.

An End-to-End Collaborative Learning Approach for Connected Autonomous Vehicles in Occluded Scenarios Exploring the Limitations of Behavior Cloning for Autonomous Driving

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T17:48:03.942671Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3fc42be8-5358-46c2-8b73-4a569fb7e8aa · outbound

This paper cites The Surprising Effectiveness of PPO in Cooperative, Multi-Agent Games.

An End-to-End Collaborative Learning Approach for Connected Autonomous Vehicles in Occluded Scenarios The Surprising Effectiveness of PPO in Cooperative, Multi-Agent Games

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T17:48:03.946693Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb79b2fb-416a-440b-8a74-bcbe8c16e97f · outbound

This paper cites Autonomous vehicle control systems for safe crossroads,.

An End-to-End Collaborative Learning Approach for Connected Autonomous Vehicles in Occluded Scenarios Autonomous vehicle control systems for safe crossroads,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:04.495259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8cf782dd-369b-48bb-a8a2-f23474f1af4c · outbound

This paper cites Intersection management for autonomous vehicles using iCACC,.

An End-to-End Collaborative Learning Approach for Connected Autonomous Vehicles in Occluded Scenarios Intersection management for autonomous vehicles using iCACC,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:04.482389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a23994ca-3e3b-4446-a51c-a64349c9de29 · outbound

This paper cites Cooperative Collision Avoidance at Intersections: Algorithms and Ex- periments,.

An End-to-End Collaborative Learning Approach for Connected Autonomous Vehicles in Occluded Scenarios Cooperative Collision Avoidance at Intersections: Algorithms and Ex- periments,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:04.470089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 90887130-4b97-4d3e-965f-a487d6437699 · outbound

This paper cites Autonomous Intersection Manage- ment For Semi-Autonomous Vehicles,.

An End-to-End Collaborative Learning Approach for Connected Autonomous Vehicles in Occluded Scenarios Autonomous Intersection Manage- ment For Semi-Autonomous Vehicles,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:04.457493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4ce605f9-131e-4fae-866e-14023c168d4f · outbound

This paper cites A Market-Inspired Approach for Intersection Management in Urban Road Traffic Networks.

An End-to-End Collaborative Learning Approach for Connected Autonomous Vehicles in Occluded Scenarios A Market-Inspired Approach for Intersection Management in Urban Road Traffic Networks

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-08-11T17:48:04.198124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 370290f7-fb5b-41de-9fd9-cb0b49560e69 · outbound

This paper cites Analysis and Modeled Design of One State-Driven Autonomous Passing-Through Algorithm for Driverless Vehicles at Intersections,.

An End-to-End Collaborative Learning Approach for Connected Autonomous Vehicles in Occluded Scenarios Analysis and Modeled Design of One State-Driven Autonomous Passing-Through Algorithm for Driverless Vehicles at Intersections,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:04.443857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d239cf52-06f4-4dc5-8fc9-3479be52d14d · outbound

This paper cites Batch-Light: An adaptive intelligent intersection control policy for autonomous vehicles,.

An End-to-End Collaborative Learning Approach for Connected Autonomous Vehicles in Occluded Scenarios Batch-Light: An adaptive intelligent intersection control policy for autonomous vehicles,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:04.428706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3b7305da-b5fa-4b07-a3a1-c673c2e6642f · outbound

This paper cites Extended time-to-collision measures for road traffic safety assessment,.

An End-to-End Collaborative Learning Approach for Connected Autonomous Vehicles in Occluded Scenarios Extended time-to-collision measures for road traffic safety assessment,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:04.416320Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b7bc88a7-76ab-497c-bf5e-9532709ce7a9 · outbound

This paper cites TIME-TO-COLLISION AND COLLISION A VOIDANCE SYSTEMS,.

An End-to-End Collaborative Learning Approach for Connected Autonomous Vehicles in Occluded Scenarios TIME-TO-COLLISION AND COLLISION A VOIDANCE SYSTEMS,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:04.403839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4da2f7c8-e3fe-4468-ac65-0e9eac377707 · outbound

This paper cites Intelligent Intersection Management Systems Considering Autonomous Vehicles: A Systematic Literature Review,.

An End-to-End Collaborative Learning Approach for Connected Autonomous Vehicles in Occluded Scenarios Intelligent Intersection Management Systems Considering Autonomous Vehicles: A Systematic Literature Review,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:04.391906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e4d8d379-1c28-430b-b85e-cec0095d076a · outbound

This paper cites Learning Negotiating Behavior Between Cars in Intersections using Deep Q-Learning.

An End-to-End Collaborative Learning Approach for Connected Autonomous Vehicles in Occluded Scenarios Learning Negotiating Behavior Between Cars in Intersections using Deep Q-Learning

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T17:48:03.987734Z

Source-reported events for the cited work

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Observation c1c06e86-0ac5-40a6-912c-29d25e287577 · outbound

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

An End-to-End Collaborative Learning Approach for Connected Autonomous Vehicles in Occluded Scenarios V2VNet: Vehicle-to-Vehicle Communication for Joint Perception and Prediction,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-11T17:48:03.991931Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 058fd3f5-b49f-4338-950b-0cca563aa482 · outbound

This paper cites Who2com: Collaborative Perception via Learnable Handshake Communication.

An End-to-End Collaborative Learning Approach for Connected Autonomous Vehicles in Occluded Scenarios Who2com: Collaborative Perception via Learnable Handshake Communication

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-08-11T17:48:04.170966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8f03c77a-891e-4c64-be88-b3945b8ed646 · outbound

This paper cites When2com: Multi-Agent Perception via Communication Graph Grouping.

An End-to-End Collaborative Learning Approach for Connected Autonomous Vehicles in Occluded Scenarios When2com: Multi-Agent Perception via Communication Graph Grouping

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-11T17:48:03.999482Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea6cec79-225b-4fa1-b353-b1a521aee386 · outbound

This paper cites Cooperative Perception with Deep Reinforcement Learning for Connected Vehicles.

An End-to-End Collaborative Learning Approach for Connected Autonomous Vehicles in Occluded Scenarios Cooperative Perception with Deep Reinforcement Learning for Connected Vehicles

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-08-11T17:48:04.142514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c4317e1b-7cdf-4d77-9e57-ba7011aa9dac · outbound

This paper cites Cooper: Cooperative Perception for Connected Autonomous Vehicles based on 3D Point Clouds.

An End-to-End Collaborative Learning Approach for Connected Autonomous Vehicles in Occluded Scenarios Cooper: Cooperative Perception for Connected Autonomous Vehicles based on 3D Point Clouds

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-08-11T17:48:04.125442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 280d3a0d-e199-4ee1-bccf-a729a552b393 · outbound

This paper cites Collaborative Automated Driving: A Machine Learning-based Method to Enhance the Accuracy of Shared Information,.

An End-to-End Collaborative Learning Approach for Connected Autonomous Vehicles in Occluded Scenarios Collaborative Automated Driving: A Machine Learning-based Method to Enhance the Accuracy of Shared Information,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:04.379602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3477c63c-bc96-49f9-9718-83edfe7b0f8f · outbound

This paper cites SMARTS: Scalable Multi-Agent Reinforcement Learning Training School for Autonomous Driving.

An End-to-End Collaborative Learning Approach for Connected Autonomous Vehicles in Occluded Scenarios SMARTS: Scalable Multi-Agent Reinforcement Learning Training School for Autonomous Driving

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-11T17:48:04.015803Z

Source-reported events for the cited work

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Observation c6e88c1c-14c0-452a-a736-1ba00e77d5b3 · outbound

This paper cites An environment for autonomous driving decision- making,.

An End-to-End Collaborative Learning Approach for Connected Autonomous Vehicles in Occluded Scenarios An environment for autonomous driving decision- making,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-11T17:48:04.019843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0434e62a-c809-422f-84d0-8b682100fe50 · outbound

This paper cites Multi-agent connected autonomous driving using deep reinforcement learning,.

An End-to-End Collaborative Learning Approach for Connected Autonomous Vehicles in Occluded Scenarios Multi-agent connected autonomous driving using deep reinforcement learning,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:04.360151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation cd1fd210-a4db-4570-bfcf-5cce750a70a6 · outbound

This paper cites OpenDRIVE 2010 and Beyond – Status and Future of the de facto Standard for the Description of Road Networks,.

An End-to-End Collaborative Learning Approach for Connected Autonomous Vehicles in Occluded Scenarios OpenDRIVE 2010 and Beyond – Status and Future of the de facto Standard for the Description of Road Networks,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:04.348298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8f3b9729-e5b2-407a-8965-daa2c1c1eec3 · outbound

This paper cites OpenCDA:An Open Cooperative Driving Automation Framework Integrated with Co-Simulation.

An End-to-End Collaborative Learning Approach for Connected Autonomous Vehicles in Occluded Scenarios OpenCDA:An Open Cooperative Driving Automation Framework Integrated with Co-Simulation

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-08-11T17:48:04.096207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c7b1ac58-561e-401a-b992-ccf913180d7d · outbound

This paper cites Intelligent Transport Systems (ITS); Vehicular Communica- tions; Basic Set of Applications; Part 2: Specification of Cooperative Awareness Basic Service.

An End-to-End Collaborative Learning Approach for Connected Autonomous Vehicles in Occluded Scenarios Intelligent Transport Systems (ITS); Vehicular Communica- tions; Basic Set of Applications; Part 2: Specification of Cooperative Awareness Basic Service

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:04.335805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 20f84147-848b-4e53-b8c0-4e7c5141d624 · outbound

This paper cites Draco 3d data compression,.

An End-to-End Collaborative Learning Approach for Connected Autonomous Vehicles in Occluded Scenarios Draco 3d data compression,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:04.323747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b2d15f1f-4a1d-4992-b3dd-79ec86962738 · outbound

This paper cites LiDAR Data Noise Models and Methodology for Sim-to-Real Domain Generaliza- tion and Adaptation in Autonomous Driving Perception,.

An End-to-End Collaborative Learning Approach for Connected Autonomous Vehicles in Occluded Scenarios LiDAR Data Noise Models and Methodology for Sim-to-Real Domain Generaliza- tion and Adaptation in Autonomous Driving Perception,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:04.311149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 35e5c7d8-4e21-497a-9a25-28f6430b9d9e · outbound

This paper cites Dedicated Short-Range Communications (DSRC) Stan- dards in the United States,.

An End-to-End Collaborative Learning Approach for Connected Autonomous Vehicles in Occluded Scenarios Dedicated Short-Range Communications (DSRC) Stan- dards in the United States,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:04.298620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Pith citing papers

No inbound Pith citation observations are available.