Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning | Paper Citation Record

Observation cead548b-27b3-4a37-84a3-5e84fd468158 · outbound

This paper cites Alleviating corporate environmental pollution threats toward public health and safety: the role of smart city and artificial intelligence,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Alleviating corporate environmental pollution threats toward public health and safety: the role of smart city and artificial intelligence,

Reference 1

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This paper cites Survey on traffic prediction in smart cities,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Survey on traffic prediction in smart cities,

Reference 2

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This paper cites Smart health: Big data enabled health paradigm within smart cities,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Smart health: Big data enabled health paradigm within smart cities,

Reference 3

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This paper cites Mobile crowdsourcing in smart cities: Technologies, applications, and future challenges,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Mobile crowdsourcing in smart cities: Technologies, applications, and future challenges,

Reference 4

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This paper cites Crowdsensing big data: sensing, data selection, and understanding,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Crowdsensing big data: sensing, data selection, and understanding,

Reference 5

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This paper cites Raccoon: Online content recommendation and edge-assisted caching for in-vehicle infotainment,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Raccoon: Online content recommendation and edge-assisted caching for in-vehicle infotainment,

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This paper cites Urban foundation models: A survey,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Urban foundation models: A survey,

Reference 7

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Observation 482caf7d-9c6f-4d8e-b18c-a0f23f64fad9 · outbound

This paper cites On the Opportunities and Challenges of Foundation Models for Geospatial Artificial Intelligence.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning On the Opportunities and Challenges of Foundation Models for Geospatial Artificial Intelligence

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Observation 15bbeca2-b2a4-4d60-b7ca-d575cc78b0d5 · outbound

This paper cites Vision Foundation Models in Remote Sensing: A Survey.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Vision Foundation Models in Remote Sensing: A Survey

Reference 9

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Observation 6f170852-a703-47a7-aded-f185ec411ce1 · outbound

This paper cites A Survey for Foundation Models in Autonomous Driving.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning A Survey for Foundation Models in Autonomous Driving

Reference 10

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Observation 7a18760d-b4f3-4c92-8bf1-43b9bd42e59c · outbound

This paper cites Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey

Reference 11

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Observation 4c3ae36b-3820-4dae-bc00-49bb1a6b4c60 · outbound

This paper cites Multi-agent rein- forcement learning for urban crowd sensing with for-hire vehicles,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Multi-agent rein- forcement learning for urban crowd sensing with for-hire vehicles,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:42.057913Z

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Observation 11754944-53bb-4b5f-bc2e-e0fca601c136 · outbound

This paper cites Intelligent marketing in smart cities: Crowd- sourced data for geo-conquesting,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Intelligent marketing in smart cities: Crowd- sourced data for geo-conquesting,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:42.041288Z

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This paper cites Data collection through mobile vehicles in edge network of smart city,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Data collection through mobile vehicles in edge network of smart city,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:42.025323Z

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Observation 4ae848a7-09bc-4281-8537-7f5821bd969f · outbound

This paper cites Towards fine- grained spatio-temporal coverage for vehicular urban sensing systems,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Towards fine- grained spatio-temporal coverage for vehicular urban sensing systems,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:42.010256Z

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Observation 4e856a17-f572-427c-88a9-f2564c64bde1 · outbound

This paper cites Privacy-preserving sta- ble crowdsensing data trading for unknown market,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Privacy-preserving sta- ble crowdsensing data trading for unknown market,

Reference 16

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Observation ae983ffd-931b-4a90-a93e-8d2e24f1f07f · outbound

This paper cites Privacy-preserving online task assignment in spatial crowdsourcing: A graph-based ap- proach,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Privacy-preserving online task assignment in spatial crowdsourcing: A graph-based ap- proach,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.978087Z

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Observation 775f3646-a5ae-4d44-8799-c9f2f38f573c · outbound

This paper cites A decentralized location privacy-preserving spatial crowdsourcing for internet of vehi- cles,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning A decentralized location privacy-preserving spatial crowdsourcing for internet of vehi- cles,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.962680Z

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Observation c19a8f6d-4b95-4cad-bc07-9803a1470885 · outbound

This paper cites A deep learning-based mobile crowdsensing scheme by predicting vehicle mo- bility,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning A deep learning-based mobile crowdsensing scheme by predicting vehicle mo- bility,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.946903Z

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Observation 653b70af-77f0-4c9e-8521-7edd94ec048b · outbound

This paper cites Exploring both individuality and cooperation for air-ground spatial crowdsourcing by multi-agent deep reinforcement learning,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Exploring both individuality and cooperation for air-ground spatial crowdsourcing by multi-agent deep reinforcement learning,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.931139Z

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Observation 40f84ea1-13a3-4c61-b1ac-a2c99c7e3ecc · outbound

This paper cites Ehta: An environment-cost-based heterogeneous task allocation in vehicular crowdsensing,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Ehta: An environment-cost-based heterogeneous task allocation in vehicular crowdsensing,

Reference 21

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Observation 768e1d5b-22c8-45de-ae6f-d6572b9dc6ea · outbound

This paper cites Privacy-preserving traffic monitoring with false report filtering via fog-assisted vehicular crowdsensing,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Privacy-preserving traffic monitoring with false report filtering via fog-assisted vehicular crowdsensing,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.898924Z

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Observation 6b8e32bf-d51c-40b5-9ec1-3efbfcdaa1d1 · outbound

This paper cites Machine learning-based models for real-time traffic flow prediction in vehicular networks,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Machine learning-based models for real-time traffic flow prediction in vehicular networks,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.881142Z

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Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Real-time traffic conges- tion prediction using big data and machine learning techniques,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.862322Z

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Observation 29e3d9d5-2833-43be-aee8-20b52ebcc35b · outbound

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Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Dynamic routing optimization in logistics us- ing machine learning: Towards efficient and sustainable supply chains,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.845874Z

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Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning An automated machine learning (automl) method of risk prediction for decision-making of autonomous vehicles,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.830192Z

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Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Giov: Achieving generative ai services in internet of vehicles via collaborative edge intelligence,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.813705Z

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Observation fdf2dfe3-def7-4f43-9bec-ca63cdb0736f · outbound

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Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Gai-iov: Bridging generative ai and vehicular networks for ubiquitous edge intelligence,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.797203Z

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Observation e09b5570-08bd-440c-bad4-7d3285155d7b · outbound

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Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Transfer learning-driven intrusion detection for internet of vehicles (iov),

Reference 29

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Observation 67a64a4f-b2cf-4e48-bf24-db705de2d512 · outbound

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Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning GeoSAM: Fine-tuning SAM with Multi-Modal Prompts for Mobility Infrastructure Segmentation

Reference 30

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Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Segment anything,

Reference 31

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Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Ringmo-sam: A foundation model for segment anything in multimodal remote-sensing images,

Reference 32

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Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Geoclip: Clip- inspired alignment between locations and images for effective worldwide geo-localization,

Reference 33

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This paper cites Learning transferable visual models from natural language supervision,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Learning transferable visual models from natural language supervision,

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This paper cites Accessed: Jul.7,2020.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Accessed: Jul.7,2020

Reference 35

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This paper cites Accessed: Jul.7,2020.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Accessed: Jul.7,2020

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.708049Z

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Observation 67d64176-3b86-403c-ba49-7103d5fa1eb0 · outbound

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Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning A taxi order dispatch model based on combinatorial optimization,

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.692309Z

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Observation 8bfe1117-121b-4b01-b31a-c0795da2a82a · outbound

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Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Data- driven transportation network company vehicle scheduling with users’ location differential privacy preservation,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.676340Z

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Observation b2f21085-ee92-460f-9f8a-1e897231e739 · outbound

This paper cites Beyond shortest paths: Route recommendations for ride-sharing,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Beyond shortest paths: Route recommendations for ride-sharing,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.660231Z

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Observation 86f3e367-fd85-4d81-b739-484628bff752 · outbound

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Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Privatehunt: Multi-source data-driven dispatching in for-hire vehicle systems,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.643180Z

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This paper cites Model predictive control of autonomous mobility-on-demand systems,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Model predictive control of autonomous mobility-on-demand systems,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.624668Z

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Observation 7041448c-4254-4e2a-bf4e-88cd471c7d8e · outbound

This paper cites Towards supply-demand equilibrium with ridesharing: An elastic order dispatching algorithm in mod system,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Towards supply-demand equilibrium with ridesharing: An elastic order dispatching algorithm in mod system,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.608067Z

Source-reported events for the cited work

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Observation e4205efd-dea8-4ee1-ae4f-82febd682844 · outbound

This paper cites Deep reinforcement learning: A brief survey,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Deep reinforcement learning: A brief survey,

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.590839Z

Source-reported events for the cited work

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Observation 214df782-c0c3-4294-b13f-fabc13bdf25a · outbound

This paper cites Deep reinforcement learning for intelligent transportation systems: A survey,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Deep reinforcement learning for intelligent transportation systems: A survey,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.573908Z

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Observation 5d0c4eb3-c20e-4d60-9133-3c234dcd47b9 · outbound

This paper cites Multi-task-oriented vehicular crowdsensing: A deep learning approach,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Multi-task-oriented vehicular crowdsensing: A deep learning approach,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.556608Z

Source-reported events for the cited work

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Observation adf5f5f6-0489-4a42-b951-74a22bc3a963 · outbound

This paper cites Impala: Scalable dis- tributed deep-rl with importance weighted actor-learner architectures,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Impala: Scalable dis- tributed deep-rl with importance weighted actor-learner architectures,

Reference 46

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Observation 6ff78cc5-6cc7-43bb-af24-a267c9a8de6d · outbound

This paper cites Multi-agent reinforce- ment learning for urban crowd sensing with for-hire vehicles,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Multi-agent reinforce- ment learning for urban crowd sensing with for-hire vehicles,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.528921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d3f0ea93-67ad-4246-929b-a3ddeb6c0033 · outbound

This paper cites Movi: A model-free approach to dynamic fleet management,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Movi: A model-free approach to dynamic fleet management,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.511716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d656e2c0-301a-4654-a78f-f7a94d5f9a00 · outbound

This paper cites Context-aware taxi dispatching at city-scale using deep reinforcement learning,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Context-aware taxi dispatching at city-scale using deep reinforcement learning,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.495280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 10b40e17-1ae2-424c-8c7b-0cb92e1858e0 · outbound

This paper cites Efficient large-scale fleet man- agement via multi-agent deep reinforcement learning,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Efficient large-scale fleet man- agement via multi-agent deep reinforcement learning,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.477726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 23d7be8c-64b0-4803-b559-f0cb2883ebf0 · outbound

This paper cites Optimizing long-term efficiency and fairness in ride-hailing via joint order dispatching and driver repositioning,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Optimizing long-term efficiency and fairness in ride-hailing via joint order dispatching and driver repositioning,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.461223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation cebec0a6-22d0-4f80-861a-a4050ec505f6 · outbound

This paper cites Multi-agent deep reinforcement learning based scheduling approach for mobile charging in internet of electric vehicles,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Multi-agent deep reinforcement learning based scheduling approach for mobile charging in internet of electric vehicles,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.445764Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 5b5ad424-23b2-472d-aeed-230b3cf66fad · outbound

This paper cites Tapfinger: Task place- ment and fine-grained resource allocation for edge machine learning,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Tapfinger: Task place- ment and fine-grained resource allocation for edge machine learning,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.430423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b45cca20-4cb9-4d90-89e4-372ace4cf5c0 · outbound

This paper cites Hetero- geneous gnn-rl-based task offloading for uav-aided smart agriculture,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Hetero- geneous gnn-rl-based task offloading for uav-aided smart agriculture,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.414230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b82997a3-8358-4dfd-8407-2b1a2f100061 · outbound

This paper cites Multi-agent graph-attention communication and teaming.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Multi-agent graph-attention communication and teaming

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.397349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 49236560-1553-4985-9743-7be6b7bdada2 · outbound

This paper cites Gnn-rl: Dynamic reward mechanism for connected vehicle security using graph neural networks and rein- forcement learning,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Gnn-rl: Dynamic reward mechanism for connected vehicle security using graph neural networks and rein- forcement learning,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.382001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d7c55f62-a7d7-4700-a79c-d3951711c214 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-09T00:39:40.889550Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ccc770ad-11f4-4851-b459-4563042ffd99 · outbound

This paper cites On the role of age of information in the internet of things,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning On the role of age of information in the internet of things,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.366262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ee0f772d-1cdd-4c57-85fe-6eadea798865 · outbound

This paper cites Freshness-aware incentive mechanism for mobile crowdsensing with budget constraint,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Freshness-aware incentive mechanism for mobile crowdsensing with budget constraint,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.348743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 325746b6-e6db-4424-8d0a-79173ed813d3 · outbound

This paper cites Scaling Laws for Neural Language Models.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Scaling Laws for Neural Language Models

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-09T00:39:40.903911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a0af5dd3-7e64-495b-babb-f81af58661c4 · outbound

This paper cites Multi-agent reinforcement learning: A selective overview of theories and algorithms,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Multi-agent reinforcement learning: A selective overview of theories and algorithms,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.333189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 91731fb2-f134-4794-acd0-f22e654382d9 · outbound

This paper cites Modeling relational data with graph convolutional networks,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Modeling relational data with graph convolutional networks,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.317158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 9db95758-3676-455d-a7dc-ed9f546a7820 · outbound

This paper cites Federated fine-tuning of large language models under heterogeneous language tasks and client resources,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Federated fine-tuning of large language models under heterogeneous language tasks and client resources,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.301619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 727c56e1-0af7-4784-949d-06e0f3dce28e · outbound

This paper cites The surprising effectiveness of ppo in cooperative multi-agent games,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning The surprising effectiveness of ppo in cooperative multi-agent games,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.286298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 96af863a-388e-4682-b071-e0524663427c · outbound

This paper cites Proximal Policy Optimization Algorithms.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Proximal Policy Optimization Algorithms

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-09T00:39:40.927309Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 04509bd4-f27a-4841-b89e-4ceb1a7e20b2 · outbound

This paper cites Learning multiple layers of features from tiny images,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Learning multiple layers of features from tiny images,

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-09T00:39:40.932400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d21c6b0-cc8a-4550-ad78-2bb2676f7c6a · outbound

This paper cites Fully convolutional networks for multisource building extraction from an open aerial and satellite imagery data set,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Fully convolutional networks for multisource building extraction from an open aerial and satellite imagery data set,

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-09T00:39:40.936906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation def20852-931e-4d07-9b0b-af41a65df8f4 · outbound

This paper cites Yolov7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Yolov7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors,

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-09T00:39:40.941563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b967257-a73a-4a4b-9e05-4cd6b321f35b · outbound

This paper cites Vehicle detection dataset,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Vehicle detection dataset,

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.240918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 3daadb1d-1e95-4f72-956d-818db68ae305 · outbound

This paper cites New york city taxi datasets,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning New york city taxi datasets,

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.224239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation dab121fb-ad10-4682-863a-30e67ec44e3d · outbound

This paper cites Coride: joint order dispatching and fleet management for multi-scale ride-hailing platforms,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Coride: joint order dispatching and fleet management for multi-scale ride-hailing platforms,

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.209632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a41a0d43-8d05-4c40-88cb-6cc604b22537 · outbound

This paper cites Algorithms for multi-armed bandit problems.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Algorithms for multi-armed bandit problems

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-09T00:39:40.961090Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d768486d-ab5b-42b6-a1b9-86b3d064e356 · outbound

This paper cites An empirical evaluation of thompson sampling,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning An empirical evaluation of thompson sampling,

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.194631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation cd996193-df7f-4850-90b8-8c1283bbc161 · outbound

This paper cites Thompson sampling and approximate inference,.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning Thompson sampling and approximate inference,

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.179512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 32639ae1-3ccc-4096-b0f8-623ad7259748 · outbound

This paper cites He also works with the Department of Communica- tions, Pengcheng Laboratory, Shenzhen, China.

Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning He also works with the Department of Communica- tions, Pengcheng Laboratory, Shenzhen, China

Reference 2018

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:41.162781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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