Paper Citation Record · LEDGER

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning

As of 20 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 1 inbound Pith citation observation for arXiv:2502.07388.

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

pith.paper-citation-record.v1
2502.07388 v1

Coverage vector

measured 57 of 57 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T13:01:27.324789Z

measured 58 of 58 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:02:08.038863Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-16T05:02:08.782678Z

Reference resolution

57 of 57 outbound references displayed

verified exact0
verified fuzzy54
unresolved3
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 12fa6c11-a625-4abc-bf53-28e4ed573918 · outbound

This paper cites Fundamental design aspects of UA V-enabled MEC systems: A review on models, challenges, and future opportunities,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Fundamental design aspects of UA V-enabled MEC systems: A review on models, challenges, and future opportunities,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:28.231473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 47abf7fc-8659-40c6-8918-8ffff4b00f50 · outbound

This paper cites A tutorial on extremely large-scale MIMO for 6G: Fundamentals, signal processing, and applications,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning A tutorial on extremely large-scale MIMO for 6G: Fundamentals, signal processing, and applications,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:28.217375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 21d77576-fba6-4413-9904-651bea9f5c35 · outbound

This paper cites UA V trajectory optimization for large-scale and low-power data collection: An attention-reinforced learning scheme,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning UA V trajectory optimization for large-scale and low-power data collection: An attention-reinforced learning scheme,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:28.202914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 436c8d63-4aa8-467c-9612-91d64731383a · outbound

This paper cites 3- d trajectory optimization and communication resources allocation in UA V-assisted IoT networks for sustainable industry 5.0,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning 3- d trajectory optimization and communication resources allocation in UA V-assisted IoT networks for sustainable industry 5.0,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:28.187760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9fca652f-881e-49cf-8266-d95dc7e842d7 · outbound

This paper cites Dual UA V cluster-assisted maritime physical layer secure communications via collaborative beamforming,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Dual UA V cluster-assisted maritime physical layer secure communications via collaborative beamforming,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:28.172419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c0e229c0-3bf9-4718-bdf5-0964f09c4c53 · outbound

This paper cites UA V swarm-enabled collaborative secure relay communications with time-domain colluding eavesdropper,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning UA V swarm-enabled collaborative secure relay communications with time-domain colluding eavesdropper,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:28.157923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 63826a94-8f58-4831-b2a3-3b7661d26616 · outbound

This paper cites Multi- objective aerial collaborative secure communication optimization via generative diffusion model-enabled deep reinforcement learning,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Multi- objective aerial collaborative secure communication optimization via generative diffusion model-enabled deep reinforcement learning,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:28.143853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation bbbafa93-6a3c-49e9-bac8-0e7c60883a73 · outbound

This paper cites A comprehensive overview on 5G-and-beyond networks with UA Vs: From communications to sensing and intelligence,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning A comprehensive overview on 5G-and-beyond networks with UA Vs: From communications to sensing and intelligence,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:28.129502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 92ae93ad-6d08-4c2c-a3e8-b8bdee73cf27 · outbound

This paper cites Outage analysis of UA V-aided networks with underlaid ambient backscatter communications,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Outage analysis of UA V-aided networks with underlaid ambient backscatter communications,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:28.115521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e946f1f8-93d1-40cd-81ab-f788c3f15ee2 · outbound

This paper cites UA V-assisted connectivity enhancement algorithms for multiple isolated sensor networks in agricultural Internet of things,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning UA V-assisted connectivity enhancement algorithms for multiple isolated sensor networks in agricultural Internet of things,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:28.100778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 03e85f80-ff7a-4c4a-a6f6-4787dfac2f71 · outbound

This paper cites UA V-assisted sleep scheduling algorithm for energy-efficient data collection in agricultural Internet of things,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning UA V-assisted sleep scheduling algorithm for energy-efficient data collection in agricultural Internet of things,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:28.085873Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4c70921c-9477-4fcc-9446-0eaa5237c1e6 · outbound

This paper cites UA V-based MEC-assisted automated traffic management scheme using blockchain,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning UA V-based MEC-assisted automated traffic management scheme using blockchain,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:28.071104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 63b2da77-0183-41a2-9d09-85cf61da7328 · outbound

This paper cites Monitoring road traffic with a UA V-based system,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Monitoring road traffic with a UA V-based system,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:28.055642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6e459192-2916-47a2-b8bc-1f7c39656374 · outbound

This paper cites Joint task offloading and resource allocation in aerial-terrestrial UA V networks with edge and fog computing for post-disaster rescue,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Joint task offloading and resource allocation in aerial-terrestrial UA V networks with edge and fog computing for post-disaster rescue,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:28.040278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 557f4c42-0405-4ff6-9ae8-71d22176fa30 · outbound

This paper cites Uav-based real-time survivor detection system in post-disaster search and rescue operations,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Uav-based real-time survivor detection system in post-disaster search and rescue operations,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:28.025046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6f4cbfd3-6a01-4e37-a9fd-8f011363befb · outbound

This paper cites Reliable and energy-efficient communications via collaborative beamforming for UA V networks,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Reliable and energy-efficient communications via collaborative beamforming for UA V networks,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:28.009805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation deb0bd5a-2b56-4063-9ef9-8b2c8ce744de · outbound

This paper cites Multi-objective optimization for multi-uav-assisted mobile edge computing,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Multi-objective optimization for multi-uav-assisted mobile edge computing,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:27.994746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 27bbbbea-6f61-4ded-97f5-5c948ca542d6 · outbound

This paper cites TJCCT: A two-timescale approach for UA V-assisted mobile edge computing,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning TJCCT: A two-timescale approach for UA V-assisted mobile edge computing,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:27.979253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d338d38f-0407-446c-a497-c9975eb5a83b · outbound

This paper cites Robust com- putation offloading and trajectory optimization for multi-UA V-assisted MEC: A multiagent DRL approach,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Robust com- putation offloading and trajectory optimization for multi-UA V-assisted MEC: A multiagent DRL approach,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:27.963909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1aa2c18f-1164-445d-9486-3a7d1b08182a · outbound

This paper cites Multi- objective optimization for data collection in UA V-assisted agricultural IoT,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Multi- objective optimization for data collection in UA V-assisted agricultural IoT,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:27.948211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b937db66-77de-4bc8-bed2-6be92802ba51 · outbound

This paper cites Max-min fair 3D trajectory design and transmission scheduling for solar-powered fixed-wing UA V-assisted data collection,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Max-min fair 3D trajectory design and transmission scheduling for solar-powered fixed-wing UA V-assisted data collection,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:27.932561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2a4e8aef-d17f-4710-b234-6d9020f14714 · outbound

This paper cites Privacy- aware and security-enhanced efficient matchmaking encryption,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Privacy- aware and security-enhanced efficient matchmaking encryption,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:27.917252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2acb0789-febc-460f-b3c5-1608991ee5cd · outbound

This paper cites Privacy-preserving fine-grained data sharing with dynamic service for the cloud-edge IoT,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Privacy-preserving fine-grained data sharing with dynamic service for the cloud-edge IoT,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:27.902592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7c633319-17f1-4319-a9c6-12d4df8111f3 · outbound

This paper cites Joint optimization on trajectory, computation and communication resources in information freshness sensitive MEC system,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Joint optimization on trajectory, computation and communication resources in information freshness sensitive MEC system,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:27.887652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f8fe3fed-673d-4a4f-b87f-77530b365fa1 · outbound

This paper cites Deep reinforcement learning based resource allocation in multi-UA V- aided MEC networks,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Deep reinforcement learning based resource allocation in multi-UA V- aided MEC networks,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:27.872852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 234fbb6c-7afd-4346-973b-8c28a6d91346 · outbound

This paper cites Service time maximization for data collection in multi-UA V-aided networks,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Service time maximization for data collection in multi-UA V-aided networks,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:27.858204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 348bb9ac-f2bf-4830-a1c4-447088555602 · outbound

This paper cites Secure video offloading in multi-uav-enabled MEC networks: A deep reinforcement learning approach,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Secure video offloading in multi-uav-enabled MEC networks: A deep reinforcement learning approach,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:27.842725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d70e25bf-77a9-49bf-b8cf-5f5435d4ccde · outbound

This paper cites Multi- UA V-enabled load-balance mobile-edge computing for IoT networks,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Multi- UA V-enabled load-balance mobile-edge computing for IoT networks,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:27.828172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 832f8e00-7ac7-410c-93e6-5558dcc58e68 · outbound

This paper cites Joint task offloading and resource allocation in uav-enabled mobile edge computing,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Joint task offloading and resource allocation in uav-enabled mobile edge computing,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:27.813201Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3204003e-bab7-4b41-b5e5-75076f102ad5 · outbound

This paper cites Multi-uav-enabled mobile-edge computing for time-constrained IoT applications,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Multi-uav-enabled mobile-edge computing for time-constrained IoT applications,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:27.798021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 322be30c-7629-49db-a799-fece548fef23 · outbound

This paper cites Computation bits maximization in UA V-assisted MEC networks with fairness constraint,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Computation bits maximization in UA V-assisted MEC networks with fairness constraint,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:27.783134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation bd663877-823d-4df4-9cc3-06dac834370e · outbound

This paper cites Multiagent reinforcement learning in controlling offloading ratio and trajectory for multi-uav mobile-edge computing,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Multiagent reinforcement learning in controlling offloading ratio and trajectory for multi-uav mobile-edge computing,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:27.767943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4b412dfa-2313-48d4-ac03-aa40070a6857 · outbound

This paper cites Energy and latency efficient joint communication and computation optimization in a multi- UA V-assisted MEC network,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Energy and latency efficient joint communication and computation optimization in a multi- UA V-assisted MEC network,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:27.753089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8ea2e0f3-73b0-4133-8686-71a44176a574 · outbound

This paper cites Joint UA V placement optimization, resource allocation, and computation offloading for thz band: A DRL approach,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Joint UA V placement optimization, resource allocation, and computation offloading for thz band: A DRL approach,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:27.737925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 38e74d1d-8a81-4a8e-9c52-9454120a57d6 · outbound

This paper cites Deep reinforcement learning based latency minimization for mobile edge computing with virtualization in maritime UA V communication network,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Deep reinforcement learning based latency minimization for mobile edge computing with virtualization in maritime UA V communication network,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:27.722683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d133aae9-6682-4688-8591-e40f14b780fd · outbound

This paper cites Multi- objective optimization for UA V-assisted wireless powered IoT networks based on extended DDPG algorithm,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Multi- objective optimization for UA V-assisted wireless powered IoT networks based on extended DDPG algorithm,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:27.707435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation de009c50-aa83-4aaf-a07f-2bb250b955c0 · outbound

This paper cites UA V trajectory planning with interference awareness in UA V-enabled time-constrained data collection systems,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning UA V trajectory planning with interference awareness in UA V-enabled time-constrained data collection systems,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:27.692130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c0237cf3-c196-4987-b97d-7ef6942d4e8a · outbound

This paper cites Mec-assisted real-time data acquisition and processing for UA V with general missions,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Mec-assisted real-time data acquisition and processing for UA V with general missions,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:27.676987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a70e76c8-6fef-4266-85f2-6f2c29a841fa · outbound

This paper cites Learning-based multi-UA V assisted data acquisition and computation for information freshness in WPT enabled space-air-ground PIoT,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Learning-based multi-UA V assisted data acquisition and computation for information freshness in WPT enabled space-air-ground PIoT,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:27.662352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f81c82cc-1748-4e7e-a212-69e23ea1d6d9 · outbound

This paper cites Multi- agent DRL for task offloading and resource allocation in multi-UA V enabled IoT edge network,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Multi- agent DRL for task offloading and resource allocation in multi-UA V enabled IoT edge network,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:27.647480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8843ec10-a8d2-44f0-b3f5-aa9f25d074a9 · outbound

This paper cites Service caching based aerial cooperative computing and resource allocation in multi-uav enabled MEC systems,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Service caching based aerial cooperative computing and resource allocation in multi-uav enabled MEC systems,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:27.632598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fc3a27e5-acbf-44f4-b286-4c93e519f5bb · outbound

This paper cites Caching in the sky: Proactive deployment of cache-enabled unmanned aerial vehicles for optimized quality-of-experience,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Caching in the sky: Proactive deployment of cache-enabled unmanned aerial vehicles for optimized quality-of-experience,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:27.618094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c00ab550-0941-4928-9623-1434ae2b7725 · outbound

This paper cites Mobile-edge com- puting: Partial computation offloading using dynamic voltage scaling,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Mobile-edge com- puting: Partial computation offloading using dynamic voltage scaling,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:27.603209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 14ac6d4f-b86f-4da1-87a5-810391ff2302 · outbound

This paper cites Modeling and analysis of stochastic mobile-edge computing wireless networks,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Modeling and analysis of stochastic mobile-edge computing wireless networks,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:27.587812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 04176bbd-8f1f-4922-b6bd-3d3ea3564020 · outbound

This paper cites Deep reinforcement learning-based contract incentive mechanism for joint sensing and computation in mobile crowdsourcing networks,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Deep reinforcement learning-based contract incentive mechanism for joint sensing and computation in mobile crowdsourcing networks,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:27.572051Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4625c1db-dab8-4147-b6ea-2bc644679bf3 · outbound

This paper cites Resource management and reflection optimization for intelligent reflecting surface assisted multi-access edge computing using deep reinforcement learning,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Resource management and reflection optimization for intelligent reflecting surface assisted multi-access edge computing using deep reinforcement learning,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:27.556255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1fb02946-b8dd-4ba1-aac9-9e8c724e5be6 · outbound

This paper cites Throughput maximization for multiedge multiuser edge computing systems,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Throughput maximization for multiedge multiuser edge computing systems,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:27.541013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c83c6a29-d2e9-4d5a-ba64-daf8fc74c45d · outbound

This paper cites Many-to-one matching markets with externalities among firms,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Many-to-one matching markets with externalities among firms,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:27.525209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6479800c-9253-4756-a1b6-429ae33459db · outbound

This paper cites Many-to-many matching with externalities for device-to-device communications,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Many-to-many matching with externalities for device-to-device communications,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:27.508676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8bc34edc-24de-4d12-9669-2453f58b533c · outbound

This paper cites Peer effects and stability in matching markets,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Peer effects and stability in matching markets,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:27.488949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ecc19f59-feb6-422d-96b3-81374fa69028 · outbound

This paper cites An efficient matching game approach to association formation in uav-enabled hierarchical distributed learning,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning An efficient matching game approach to association formation in uav-enabled hierarchical distributed learning,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:27.471566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e2cb433b-fe3c-470f-ae64-80b652499341 · outbound

This paper cites Soft Actor-Critic Algorithms and Applications.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Soft Actor-Critic Algorithms and Applications

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-08T13:01:27.300302Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 56828b2c-97bb-420a-a75a-5aeb440a5f3d · outbound

This paper cites Energy-constrained UA V data collection systems: NOMA and OMA,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Energy-constrained UA V data collection systems: NOMA and OMA,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:27.454766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0729dc4e-c325-425d-94ce-76ad0ef46ee0 · outbound

This paper cites Addressing Function Approximation Error in Actor-Critic Methods.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Addressing Function Approximation Error in Actor-Critic Methods

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-08T13:01:27.310091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8e1fec89-2641-4895-977a-30401108b650 · outbound

This paper cites Proximal Policy Optimization Algorithms.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Proximal Policy Optimization Algorithms

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-08T13:01:27.315290Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b8f23172-dade-4c86-8124-8c18dc2891ce · outbound

This paper cites UA V-enabled fair offloading for MEC networks: A DRL approach based on actor-critic parallel architecture,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning UA V-enabled fair offloading for MEC networks: A DRL approach based on actor-critic parallel architecture,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:27.437095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ef9dc630-da05-4859-b3d4-b29114bd2c7c · outbound

This paper cites Dual- timescales optimization of task scheduling and resource slicing in satellite-terrestrial edge computing networks,.

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning Dual- timescales optimization of task scheduling and resource slicing in satellite-terrestrial edge computing networks,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:01:27.418421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

Observation 7a94c4be-52f0-4ba9-98ca-44cf56916e9d · inbound

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

Toward Realization of Low-Altitude Economy Networks: Core Architecture, Integrated Technologies, and Future Directions UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning

Reference 38

Resolution: verified exact; local_arxiv, observed 2026-08-16T05:02:08.786691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.