Pith. sign in

Paper Citation Record · LEDGER

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

As of 10 August 2026, this Paper Citation Record lists 75 of 75 outbound references and 1 inbound Pith citation observation for arXiv:2502.04399.

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

pith.paper-citation-record.v1
2502.04399 v1

Coverage vector

measured 75 of 75 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T00:39:40.975455Z

measured 76 of 76 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-18T23:11:53.057766Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T23:12:53.442563Z

Reference resolution

75 of 75 outbound references displayed

  • verified exact0
  • verified fuzzy58
  • unresolved17
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T00:39:42.170282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.629510Z digest=sha256:f8e751efb4836635cf52afdeb44b6d0d0e563147704e677d4126757695be0426

Observation 60033cfd-9cf6-464a-8b4c-36946e1e0956 · outbound

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T00:39:42.154642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.634692Z digest=sha256:8217c1f1fa12cd94e5df9306b89014e9e5349d8393166f87854903a949f2fe7e

Observation e8233519-b28a-4af9-902e-a0d66f7d157f · outbound

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T00:39:42.138470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.639924Z digest=sha256:c1fcaad5ed00b8581cf3d540560e183b2b827012e90585531fb41f10f7559fa9

Observation 5512181d-919d-46d2-85cb-bd202937254d · outbound

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T00:39:42.122573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.644858Z digest=sha256:663a9e8f0b28807e89d2c8a1d380a8c5beb703780cb91dd54d3f434f1a4f22f2

Observation bd68fb11-e10c-49ba-b0a0-a3b28e07d16c · outbound

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T00:39:42.106026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.650279Z digest=sha256:c97aa176ca8a0ca6a251d431aea8a06a74070601e81776313582c1d03cdd2166

Observation c43771cb-7289-42a4-b61e-4c091ee224c1 · outbound

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,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T00:39:42.089825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.655111Z digest=sha256:9be546bfa189c232f6b16da377d4eac1b6e60b352ea24f350ef1867e5ce4440c

Observation b5559948-fb6e-4e94-ae8e-024022027ff1 · outbound

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T00:39:42.073721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.660597Z digest=sha256:8e4a4899331e3b895618b0d3a213bf11620549ac7a8fa6cbb55215ac491f016f

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

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-09T00:39:40.664702Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T00:39:40.664702Z digest=sha256:f6eb5e282fee894b47f946d46b3a8673dd842a0858ab8694132480034475c9c7

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

Resolution
unresolved
no resolver link, observed 2026-08-09T00:39:40.669210Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T00:39:40.669210Z digest=sha256:100e8d18910bb50ae92d98cfd9183d1124cca003396ea5c9c3d930c352870584

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

Resolution
unresolved
no resolver link, observed 2026-08-09T00:39:40.673587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T00:39:40.673587Z digest=sha256:a27c01c35662a2996c00addef267896bf3e514c933140ff0d6ca96670be785af

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

Resolution
unresolved
no resolver link, observed 2026-08-09T00:39:40.678115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T00:39:40.678115Z digest=sha256:c10172c9d6056a175c62c81a52f670fcfddc1a9052a1ccd737322ab48bde5d08

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.683243Z digest=sha256:36a21c1af96150a73c30a6df5f40910746505e99f114d133d85a36fa6ce7dc69

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.688195Z digest=sha256:2c020090e989abe441fce9845234c5c227eea8f89759da7c934ad63ab3a317d8

Observation 32371c49-d01b-4723-bdbd-fc044f537033 · outbound

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.692737Z digest=sha256:6fc03b979ab59e0c4c2d1da9145125697ec890fafe33b74471d91ae631969507

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.697249Z digest=sha256:84bf5ede5766529084c76e206222e8b735a294da53386915898a8ca4f560f81f

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T00:39:41.994725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.701766Z digest=sha256:cc09c3c7859527de4eb8807781744b0f1db98d472e470a1d2a9d0a6ffc824383

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.706516Z digest=sha256:ec548124de120a22bc0a4fddbf89676375f33cf0bc64c4eb0ca7b384167369ee

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.711370Z digest=sha256:81d2efee33d2b611cfd26844551464f25ff789ce1e7575c131f7066655c0fc06

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.715999Z digest=sha256:d04eb07b3ee00bffabc5e4af4594308fd6fc45e792962cddfbab77456bef9312

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.720278Z digest=sha256:db227612181afef00cb136c4693160efecb71e2cb4e4fce8ca6db476fcce5f93

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T00:39:41.914599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.725185Z digest=sha256:bd878b404a16a68458cd501aad3319bc4b3db901f9f1b7d4bca76854d0d73ece

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.729724Z digest=sha256:7acc4a520bbd00108dcac8139f60a2a70809c4058b63291aae1503bf2eb7d730

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.734406Z digest=sha256:be511aa9f07d8076139c6490b2f6a306855b635bd3a8fd19f54acf925d5318ea

Observation 2f4eb225-a398-4912-8538-5cd0bd28750b · outbound

This paper cites Real-time traffic conges- tion prediction using big data and machine learning techniques,.

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.739331Z digest=sha256:3202d46ba6b0c870f3895d1f69e2418540b8e9b6bbc4802e6746e318dd301197

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

This paper cites Dynamic routing optimization in logistics us- ing machine learning: Towards efficient and sustainable supply chains,.

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.744033Z digest=sha256:6dd4267bb12386c74b98d81f794bc8744eed292aaa3a763ff801d6d9d9e969b0

Observation 4c10fc43-62d6-428d-8408-ca3d09496986 · outbound

This paper cites An automated machine learning (automl) method of risk prediction for decision-making of autonomous vehicles,.

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.748524Z digest=sha256:dab3f678bb186535316a48dac52b433e42f683dc955ff7d82f65caa348ef6f7f

Observation bd73ea73-c1fc-48cf-bc4b-3351153d60d7 · outbound

This paper cites Giov: Achieving generative ai services in internet of vehicles via collaborative edge intelligence,.

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.753078Z digest=sha256:329559006980061894d8f080c52113d0bc4044d6dcf4e710bd7570b647015b41

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

This paper cites Gai-iov: Bridging generative ai and vehicular networks for ubiquitous edge intelligence,.

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.757545Z digest=sha256:1cfdfd22a72eee84166fae503341a52e73614d11bd5c37b2239e0ea37fbd702b

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

This paper cites Transfer learning-driven intrusion detection for internet of vehicles (iov),.

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

Resolution
unresolved
no resolver link, observed 2026-08-09T00:39:40.762380Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T00:39:40.762380Z digest=sha256:8aefe1b70301d940121ef11c2ebac87f92e2ec2b665b6b13b8e9e9f37f1b43c3

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

This paper cites GeoSAM: Fine-tuning SAM with Multi-Modal Prompts for Mobility Infrastructure Segmentation.

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

Resolution
unresolved
no resolver link, observed 2026-08-09T00:39:40.767276Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T00:39:40.767276Z digest=sha256:2384d16e9ce80b534caadc1870071ce2501c7ade9bed0e1fef70a785a0c2d3a4

Observation db6dd3b3-8ae0-47af-9819-18aa76b95a78 · outbound

This paper cites Segment anything,.

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

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-09T00:39:40.772721Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T00:39:40.772721Z digest=sha256:c2e27d896fb91859bf64cf2416c4584aedaa4814988fe2deeb6f88818f07f59b

Observation 470bb06b-770f-4098-a1bd-2500aedfb6e1 · outbound

This paper cites Ringmo-sam: A foundation model for segment anything in multimodal remote-sensing images,.

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

Resolution
unresolved
no resolver link, observed 2026-08-09T00:39:40.777180Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T00:39:40.777180Z digest=sha256:f19144c7135535f3d51f6ec5797f5f0926e7d8fceea3d87731dfcc42bfad4967

Observation 63714eb0-5fa2-45d8-a714-e787a9311d65 · outbound

This paper cites Geoclip: Clip- inspired alignment between locations and images for effective worldwide geo-localization,.

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T00:39:41.749652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.781521Z digest=sha256:91c2e7102445d778272738dce99a174b0572f772975b3491585a741f0e09551c

Observation 52194441-cd12-41d0-8b26-ed419e122293 · outbound

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,

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-09T00:39:40.786289Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T00:39:40.786289Z digest=sha256:de3f53d8f56f77f96c018d97eb8a5e6b0c78b1c0d23f0310afab0badb35073bc

Observation 56e1f0d9-8d16-4e69-bb68-56facb9eb874 · outbound

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T00:39:41.723330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.790788Z digest=sha256:535b0ce0b2df8fe35b18e8ec2d05abc856359078b631328cb16c97a65bfec7e0

Observation 18665354-0934-45d5-a862-9270630c018e · outbound

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.795357Z digest=sha256:829dd3ca0fa80ea69a2b280eb3b9516f64c7668f733b7c0b4d4ac313b25f5dcb

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

This paper cites A taxi order dispatch model based on combinatorial optimization,.

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,

Reference 37

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.800353Z digest=sha256:bbe05c59f10a2fa74b8ce35d3baf7e9b2e76d2512b1c82cddc6c1c9ff86dab44

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

This paper cites Data- driven transportation network company vehicle scheduling with users’ location differential privacy preservation,.

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.805017Z digest=sha256:41362d498e9195a4899a4d3cd8c8e47240ba88502ecc9dbf45cf04536bf53d20

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.809607Z digest=sha256:c58d1b14980eee97deac7604d418e3a14632e5a458ddae0ef069edfacb945e39

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

This paper cites Privatehunt: Multi-source data-driven dispatching in for-hire vehicle systems,.

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.814268Z digest=sha256:10bfe45c911a722567a0719a3f78bc1592dd10c9d2b1b8e7a3b1f5bf823eba60

Observation 84c153a1-badc-4054-afaa-28de5915493c · outbound

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.819117Z digest=sha256:0d73534d1c7e98ae9f35cde426cd01eec6e7b0063368efa3e3f7dd8ba7cf539d

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

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.823662Z digest=sha256:6eb5672ab943273d7a7da60c9315ad27ef04b74e45c6f39937a2df7153bccd05

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,

Reference 43

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.828154Z digest=sha256:7dfb43a1e7ef89465be27033e24fb7f5ac70357c0dda6e0e809f3ab0b3b73f9b

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.832640Z digest=sha256:f7d70d4cbeda401e5cafa3647ed60e39195ee32cc61293c6bc471e26bb5fa42a

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

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.836996Z digest=sha256:2aa78ba247659e5e119fb03388ce2b9b391d8a49e53f8f4b44e2fc92501ddaf0

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

Resolution
unresolved
no resolver link, observed 2026-08-09T00:39:40.841135Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T00:39:40.841135Z digest=sha256:0065791d714500c1e5a92545a095a7e3561d0dbcd5dbab975449a4b31f540f06

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.845618Z digest=sha256:f0a6d7ea66ff53294251afcaaf04e2d0c05db084b51ec4f8325b7fa530effff9

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.849791Z digest=sha256:87b0c4557e21d05b66f0d3f00504c083e4bea8dbf45acbb4e12acd654cd2e010

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.853926Z digest=sha256:f3dc69c2f5e20b3de66b9108251f3777bff09b4aca7587f652adffccfd2b2e93

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.858129Z digest=sha256:dcdcb82c1aaf2656984608f2374e21181ea41d41a8d9a1c8dcfd732101cabdfc

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.862334Z digest=sha256:f704bac1ef8c01325552db3fba297732176b1011653be48ce25216e8d67ffcc0

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.866472Z digest=sha256:d885bd66a925371ad165f8683c05a81558bea36e14b0990dc7f13c1588646d25

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.871126Z digest=sha256:137fd9be076bd95c97b0689f567f31f79b374c02bf93b79f90f3c250144bff9b

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.875895Z digest=sha256:5e8baa810faac445525600ea21dbf878e53803a4f848ca28b9b6728cdf28547a

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.880547Z digest=sha256:f64a880aed8713c2b032a4dda764d97a9cbde2f188885ca94de734547e0bbde5

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.885089Z digest=sha256:a5ea26d1b423f6d1e08c63a41a1ecb238060cac78fc180e67c0bc6307b6d7377

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.

source=pdf_text observed=2026-08-09T00:39:40.889550Z digest=sha256:c2d94b38b3c716aaf1d7abaf12206a1b6e731c6d540fd1b60a1c03c4424fc4be

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.894347Z digest=sha256:f87e966c04a29e4816ff888d76b1d5e0f7d3854a2a2b37d0c99b3cd46877769a

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.899295Z digest=sha256:f9613445a542da1b04dff7910b04ce18ac3d4cf09e9425b953af8983e9f5dcfe

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.

source=pdf_text observed=2026-08-09T00:39:40.903911Z digest=sha256:40054fef09ebc64debfbc0779c48ade4bd34856722701fe36a88b308183197cc

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.909268Z digest=sha256:982a907b4c93f0aa423b394c3519a305b97facb355af4c69c0028c54f5648f35

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.913686Z digest=sha256:b849bf46d892eaf84410ff3a78b7ab9ca60c0160e1aed47f5b9d7a4248bf750a

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.918389Z digest=sha256:2e64af6de7199ca417fee11713c640e9c8129b8f5aa2d55e396f7d2a03302117

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.922934Z digest=sha256:767d3b41411ba3f6a2c68f76b4e3d5fe2eb95e6bed56a7a0bd8978ae9abb0c87

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.

source=pdf_text observed=2026-08-09T00:39:40.927309Z digest=sha256:ebddefa7150b863a178b2c61332b046d5eb40ca9ede92d7665d169149ff6e601

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.

source=pdf_text observed=2026-08-09T00:39:40.932400Z digest=sha256:c14a7b6d4c4658c3f7c6dc577d17f206a2049371455d0fef904c8a75aa247242

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.

source=pdf_text observed=2026-08-09T00:39:40.936906Z digest=sha256:a03e5b3af968ad92f685f43fd6ab42727ff1179aff40b23311cc3713b919a966

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.

source=pdf_text observed=2026-08-09T00:39:40.941563Z digest=sha256:7eea2f1b96ce77cbeb50bbbc8f2bfa1541e5e60932f8f952dab51e1ecc0cd0b0

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.946771Z digest=sha256:c9950b5dbf9586c2def43aa7eda5c0d55864fbc89a455003b9627748a6f211ea

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.951561Z digest=sha256:8ed2c73a8ff4aa1e78e98ada54f50a9344694fbe1f3494802860c8704e349922

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.956421Z digest=sha256:443b917f503d6c688212dbe00ff7023508f2784aa71205529498a02a32c7ea7b

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.

source=pdf_text observed=2026-08-09T00:39:40.961090Z digest=sha256:2f8e65182af7e27ee91b1ce9b023d8c9bed895c5a052fb524756f02cf83d1fa8

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.966217Z digest=sha256:cfb1400b0eb0048746e3494bbe0a9e4db966186a20d7554bd85b4552763ece76

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.970703Z digest=sha256:db86b0a80a21217d26ce5830c56505792f8f906fb68fcdc3fb243d828e4fe36e

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:39:40.975455Z digest=sha256:ad9a30a167cc3a709ce3874be2dd37ab061b11f3f548b452717436ca399b499d

Pith citing papers

Observation 74af98d4-ab23-4769-b55b-9078216ce730 · inbound

Decentralized Rank Scheduling for Energy-Constrained Multi-Task Federated Fine-Tuning in Edge-Assisted IoV Networks cites this paper.

Decentralized Rank Scheduling for Energy-Constrained Multi-Task Federated Fine-Tuning in Edge-Assisted IoV Networks Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-05-18T23:12:53.445171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-18T23:11:53.057766Z digest=sha256:fe7af68ed048426d4346745e9b5cc5719935c0c234dc446dc632ee73de00d4de