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Paper Citation Record · LEDGER

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception

As of 14 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 1 inbound Pith citation observation for arXiv:2502.10456.

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

pith.paper-citation-record.v1
2502.10456 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T10:26:10.915966Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:11:40.470050Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T21:11:40.532303Z

Reference resolution

40 of 40 outbound references displayed

  • verified exact2
  • verified fuzzy30
  • unresolved8
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d33e7b27-1624-42bf-8b51-79e1ed6cc375 · outbound

This paper cites Milestones in autonomous driving and intelligent vehicles: Survey of surveys,.

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception Milestones in autonomous driving and intelligent vehicles: Survey of surveys,

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 33c980dc-1ad7-4097-ad58-5d3b6cd57cc3 · outbound

This paper cites Towards Vehicle-to-everything Autonomous Driving: A Survey on Collaborative Perception.

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception Towards Vehicle-to-everything Autonomous Driving: A Survey on Collaborative Perception

Reference 2

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation fc06795a-bc2c-410c-8109-dfbdc1422a11 · outbound

This paper cites Collaborative perception in autonomous driving: Methods, datasets, and challenges,.

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception Collaborative perception in autonomous driving: Methods, datasets, and challenges,

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 28a2d732-6f8b-47d8-a2d6-4e2d80a3054b · outbound

This paper cites Vehicular communications: A physical layer perspective,.

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception Vehicular communications: A physical layer perspective,

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation ba6dbd71-c94b-4e27-8e71-3d51aa391b55 · outbound

This paper cites Technical specification group radio access network; study on LTE-based V2X services; (Release 14),.

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception Technical specification group radio access network; study on LTE-based V2X services; (Release 14),

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 52d1a093-3803-4b42-ade1-3c9c6f81db41 · outbound

This paper cites Technical specification group radio access network; NR; study on NR vehicle-to-everything(V2X); (Release 16),.

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception Technical specification group radio access network; NR; study on NR vehicle-to-everything(V2X); (Release 16),

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 0868b660-d1df-4056-9395-eacb3dbfaeef · outbound

This paper cites Networking and communications in autonomous driving: A survey,.

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception Networking and communications in autonomous driving: A survey,

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 62a9d377-72da-47e1-90d1-c428e48c9f7c · outbound

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

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception Learning distilled collaboration graph for multi-agent perception,

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 43e7fd2b-0a00-4d90-a5ac-b3e2853f9d79 · outbound

This paper cites V2X-ViT: Vehicle-to-everything cooperative perception with vision transformer,.

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception V2X-ViT: Vehicle-to-everything cooperative perception with vision transformer,

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 3e865228-2d28-4c41-9a91-5d8ee1452499 · outbound

This paper cites V2VNet: Vehicle-to-vehicle communication for joint perception and prediction,.

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception V2VNet: Vehicle-to-vehicle communication for joint perception and prediction,

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation cc0b2b34-a20e-4385-a3bd-bfe29f4fbd11 · outbound

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

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception Where2comm: Communication-efficient collaborative perception via spatial confidence maps,

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation b9f45613-389c-4d74-acc8-b5fef485925f · outbound

This paper cites Technical specification group ser- vices and system aspects; enhancement of 3GPP support for V2X scenarios; stage 1 (Release 18),.

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception Technical specification group ser- vices and system aspects; enhancement of 3GPP support for V2X scenarios; stage 1 (Release 18),

Reference 12

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raw_fallback, observed 2026-08-08T10:26:11.314050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 189246a6-b736-4f62-9632-9e492eeb5b8e · outbound

This paper cites Real-time spatio-temporal liDAR point cloud compression,.

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception Real-time spatio-temporal liDAR point cloud compression,

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 5c69e328-5d2e-4604-9f1b-24331b844d3b · outbound

This paper cites Low complexity outage optimal distributed channel allocation for vehicle-to-vehicle communi- cations,.

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception Low complexity outage optimal distributed channel allocation for vehicle-to-vehicle communi- cations,

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation c405e81c-760c-452a-8c75-b2bcea838caf · outbound

This paper cites Cluster-based radio resource management for D2D-supported safety-critical V2X communi- cations,.

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception Cluster-based radio resource management for D2D-supported safety-critical V2X communi- cations,

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation e680f6ce-85cf-42a7-b107-ff90c1af8156 · outbound

This paper cites Resource allocation for D2D-enabled vehicular communications,.

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception Resource allocation for D2D-enabled vehicular communications,

Reference 16

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Source-reported events for the cited work

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Observation 89292f0b-f7f6-4b0f-9227-30aa9e6f8174 · outbound

This paper cites Deep reinforcement learning based resource allocation for V2V communications,.

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception Deep reinforcement learning based resource allocation for V2V communications,

Reference 17

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 993c9dbe-98bb-45c0-886c-dacfbd63eb35 · outbound

This paper cites Spectrum sharing in vehicular networks based on multi-agent reinforcement learning,.

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception Spectrum sharing in vehicular networks based on multi-agent reinforcement learning,

Reference 18

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Observation 76637fb3-0e7b-48cf-880f-be0d5837fdc6 · outbound

This paper cites Meta Reinforcement Learning for Fast Spectrum Sharing in Vehicular Networks.

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception Meta Reinforcement Learning for Fast Spectrum Sharing in Vehicular Networks

Reference 19

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 3e6ad16f-dca5-4c2c-8ac5-fc199902ce9b · outbound

This paper cites Multi-agent deep reinforcement learning for dynamic power allocation in wireless networks,.

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception Multi-agent deep reinforcement learning for dynamic power allocation in wireless networks,

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 10871786-8bd8-4d8e-a028-d4159ce07882 · outbound

This paper cites AI empowered wireless communications: From bits to semantics,.

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception AI empowered wireless communications: From bits to semantics,

Reference 21

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Unavailable: canonical work link unavailable.

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Observation e6497d8d-98a3-4760-95d8-6129940002f4 · outbound

This paper cites Semantic communica- tion for cooperative perception based on importance map,.

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception Semantic communica- tion for cooperative perception based on importance map,

Reference 22

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raw_fallback, observed 2026-08-08T10:26:11.216531Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 129856f8-8d07-4f60-a45f-6a4e4cdeb94c · outbound

This paper cites AutoCast: Scalable Infrastructure-less Cooperative Perception for Distributed Collaborative Driving.

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception AutoCast: Scalable Infrastructure-less Cooperative Perception for Distributed Collaborative Driving

Reference 23

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Unavailable: canonical work link unavailable.

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Observation 947db505-6596-43ff-9249-0878f18a51dc · outbound

This paper cites MASS: Mobility-aware sensor scheduling of cooperative perception for connected automated driving,.

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception MASS: Mobility-aware sensor scheduling of cooperative perception for connected automated driving,

Reference 24

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raw_fallback, observed 2026-08-08T10:26:11.204398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 9d6db4b9-8ac8-4ce0-8535-2fef78c968e8 · outbound

This paper cites C-MASS: Combinatorial Mobility-Aware Sensor Scheduling for Collaborative Perception with Second-Order Topology Approximation.

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception C-MASS: Combinatorial Mobility-Aware Sensor Scheduling for Collaborative Perception with Second-Order Topology Approximation

Reference 25

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local_arxiv, observed 2026-08-08T10:26:10.969281Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation cf89a752-5100-442b-8bdf-8f2c3a7fd705 · outbound

This paper cites Select2Col: Leveraging spatial-temporal importance of se- mantic information for efficient collaborative perception,.

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception Select2Col: Leveraging spatial-temporal importance of se- mantic information for efficient collaborative perception,

Reference 26

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raw_fallback, observed 2026-08-08T10:26:11.191556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation cec131ce-d127-4f43-83f8-23d4a7d26fd6 · outbound

This paper cites Accuracy-aware cooperative sensing and computing for connected autonomous vehicles,.

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception Accuracy-aware cooperative sensing and computing for connected autonomous vehicles,

Reference 27

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raw_fallback, observed 2026-08-08T10:26:11.177695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-08T10:26:10.863481Z digest=sha256:64f8c176931c6013e827945aee8e30e64762e6c99f3a10429b93665391fcfb54

Observation eb11e607-ed77-4f0f-96d9-0f04b81a613d · outbound

This paper cites Pointpillars: Fast encoders for object detection from point clouds,.

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception Pointpillars: Fast encoders for object detection from point clouds,

Reference 28

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raw_fallback, observed 2026-08-08T10:26:11.165211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 456e9f69-7fba-4172-b01b-a2ec7c30bfb2 · outbound

This paper cites Spectrum and power allocation for vehicular communications with delayed CSI feedback,.

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception Spectrum and power allocation for vehicular communications with delayed CSI feedback,

Reference 29

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raw_fallback, observed 2026-08-08T10:26:11.152726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 2c1262fd-00f1-43af-85be-ee2508bef6db · outbound

This paper cites A comprehensive survey of LIDAR-based 3D object detection methods with deep learning for autonomous driving,.

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception A comprehensive survey of LIDAR-based 3D object detection methods with deep learning for autonomous driving,

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-08T10:26:10.875769Z digest=sha256:2d6059c7e38c5788052f6866e92b692d292f03a8475d074a0f6b833886d48699

Observation b0ab4a9d-e6a5-4e8c-a991-3b7070fa8004 · outbound

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

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception F-cooper: Feature based cooperative perception for autonomous vehicle edge computing system using 3d point clouds,

Reference 31

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raw_fallback, observed 2026-08-08T10:26:11.127140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-08T10:26:10.879612Z digest=sha256:b0f8643d697afefe101e0fcf7ece0dc76d96f50df2f48a1545ce4cb05b37c5aa

Observation c7464af6-632b-460c-b2b4-5b9b3cf3dc49 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception Proximal Policy Optimization Algorithms

Reference 32

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no resolver link, observed 2026-08-08T10:26:10.883505Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T10:26:10.883505Z digest=sha256:30072f5a00d05058df4ab818a528b4d8def217941e0376be641772b89c8de210

Observation 83f1ddcc-baab-45c6-8220-7a1fb3add0a0 · outbound

This paper cites AP-loss for accurate one-stage object detection,.

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception AP-loss for accurate one-stage object detection,

Reference 33

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raw_fallback, observed 2026-08-08T10:26:11.113054Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-08T10:26:10.887647Z digest=sha256:43949e131a89eeff0d79982cbdb713b1f5c2410f823712741c939d70a2631012

Observation 1ff925d1-2679-41f6-aaca-db586815dfca · outbound

This paper cites V2X-Sim: Multi-agent collaborative perception dataset and benchmark for autonomous driving,.

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception V2X-Sim: Multi-agent collaborative perception dataset and benchmark for autonomous driving,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T10:26:11.100553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-08T10:26:10.891610Z digest=sha256:0084b8609468502e4f173966e29beb3f2791f521437ca283ec2e63fe618a2017

Observation 5d156d13-ab10-4fda-ac19-865179a5a0a0 · outbound

This paper cites Deep sparse rectifier neural networks,.

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception Deep sparse rectifier neural networks,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T10:26:11.087388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-08T10:26:10.895520Z digest=sha256:6335e67cfbf43519ccfec4eac73845357044692e7cd0ace0aa4be5a9960f7dbc

Observation c51a8501-3948-49c8-beb0-7fdc5f7d8aa8 · outbound

This paper cites Deep-learning-based wireless resource allocation with application to vehicular networks,.

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception Deep-learning-based wireless resource allocation with application to vehicular networks,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T10:26:11.074186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-08T10:26:10.899457Z digest=sha256:2e16d44d59182c177e5d0a0b4592fd68afaa96e7c0dbdd8c0b51706ece07d1c0

Observation d57a8581-036b-4bae-9537-82aa95d95780 · outbound

This paper cites Deep reinforcement learning with double Q-learning,.

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception Deep reinforcement learning with double Q-learning,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T10:26:11.061247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-08T10:26:10.903608Z digest=sha256:d801c1c9367592ae1eff72a7e67f7f92f020ba08f41e9ed0f64a784a9c5daf3a

Observation 42b85ec6-c0d3-460e-97d7-be9e52b7b0d6 · outbound

This paper cites Human-level control through deep reinforcement learning,.

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception Human-level control through deep reinforcement learning,

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-08T10:26:10.908102Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T10:26:10.908102Z digest=sha256:e1fef47f338dd45c905ccefe723bdd725fd17ca043dfc7b919e89e2ce84955ff

Observation e0d146f8-b685-4078-8b66-40937a3c686d · outbound

This paper cites CARLA: An open urban driving simulator,.

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception CARLA: An open urban driving simulator,

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-08T10:26:10.912112Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T10:26:10.912112Z digest=sha256:d096a206a9dc5b752108d37fe0ed9cf6c24ad3e75c0b85b5073ffa52d7bd4deb

Observation 310ed246-0195-454b-a4de-316f2b271538 · outbound

This paper cites Microscopic traffic simulation using SUMO,.

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception Microscopic traffic simulation using SUMO,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T10:26:11.032547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-08T10:26:10.915966Z digest=sha256:5c4c266bca98911a309a8c4e2c6727795239a44e94439bbfd8237a33d96cf8a8

Pith citing papers

Observation 1e23c1ae-88ba-435f-948b-f76c18bd9853 · inbound

SComCP: Task-Oriented Semantic Communication for Collaborative Perception cites this paper.

SComCP: Task-Oriented Semantic Communication for Collaborative Perception Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception

Reference 29

Resolution
verified exact
local_arxiv, observed 2026-08-06T21:11:40.537370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:11:40.470050Z digest=sha256:ba01813ecca7eb9e480dcb1e05ea2a895d679be2ea54dbb8f28519510c299979