Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T20:37:04.168493Z
Paper Citation Record · LEDGER
Continual Reinforcement Learning for Digital Twin Synchronization Optimization
As of 17 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2501.08045.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
45 of 45 outbound references displayed
- verified exact0
- verified fuzzy40
- unresolved4
- parse uncertain0
- malformed identifier1
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 636494d6-bd83-44d5-aaac-1b6fc96fd060 · outbound
This paper cites Digital twin networks: A survey,.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization Digital twin networks: A survey,
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.827634Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 1663a4cb-4dfd-4745-bbd0-cea2a0826412 · outbound
This paper cites Meta- verse for wireless systems: Vision, enablers, architecture, and future directions,.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization Meta- verse for wireless systems: Vision, enablers, architecture, and future directions,
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.814130Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 7723d7e0-eedc-4f20-b0f7-334c46bad108 · outbound
This paper cites Digital twin for networking: A data-driven performance modeling perspective,.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization Digital twin for networking: A data-driven performance modeling perspective,
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.799811Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 097ddd5d-982e-4125-bdb4-04a5bab1ddba · outbound
This paper cites Mobility-aware service provisioning in edge computing via digital twin replica placements,.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization Mobility-aware service provisioning in edge computing via digital twin replica placements,
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.786436Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 4e2fff57-f489-4e49-b354-020044a48ffa · outbound
This paper cites Toward communication-efficient digital twin via ai-powered transmission and reconstruction,.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization Toward communication-efficient digital twin via ai-powered transmission and reconstruction,
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.772807Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 9923824f-6fda-411c-b6f6-70cbc70e789c · outbound
This paper cites End-to-end network sla quality assurance for c-ran: A closed-loop management method based on digital twin network,.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization End-to-end network sla quality assurance for c-ran: A closed-loop management method based on digital twin network,
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.758894Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 541a7a06-384d-4ec0-8fbe-fda87721b93f · outbound
This paper cites Digital-twin-enabled intelligent dis- tributed clock synchronization in industrial IoT systems,.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization Digital-twin-enabled intelligent dis- tributed clock synchronization in industrial IoT systems,
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.730950Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation ff75700d-c476-4a7e-8637-70c2f28a2441 · outbound
This paper cites Digital twin-empowered network planning for multi-tier computing,.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization Digital twin-empowered network planning for multi-tier computing,
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.716088Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 59e2ef49-9e08-4278-8e65-0721d52a4cce · outbound
This paper cites A federated digital twin framework for uavs-based mobile scenarios,.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization A federated digital twin framework for uavs-based mobile scenarios,
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.702908Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 99f875d7-b4ce-4aec-b964-c6df19ba721b · outbound
This paper cites Cybertwin assisted wire- less asynchronous federated learning mechanism for edge computing,.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization Cybertwin assisted wire- less asynchronous federated learning mechanism for edge computing,
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.689356Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 4952007d-3ae5-4098-b3a6-a2518209f8b0 · outbound
This paper cites Adaptive federated learning and digital twin for industrial internet of things,.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization Adaptive federated learning and digital twin for industrial internet of things,
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.676071Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 76cc0291-29c6-4591-9ca2-37a3f7948ded · outbound
This paper cites Adaptive digital twin for vehicular edge computing and networks,.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization Adaptive digital twin for vehicular edge computing and networks,
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.662207Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 62113179-0896-4d4e-9e8a-2bdf3988e497 · outbound
This paper cites Digital twin-enhanced deep reinforcement learning for resource management in networks slicing,.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization Digital twin-enhanced deep reinforcement learning for resource management in networks slicing,
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.648367Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 30ece679-8804-4954-9867-fcb59b0c590b · outbound
This paper cites Digital twin-driven collaborative scheduling for heterogeneous task and edge-end resource via multi-agent deep reinforcement learning,.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization Digital twin-driven collaborative scheduling for heterogeneous task and edge-end resource via multi-agent deep reinforcement learning,
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.634356Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation fb138a54-ce63-4a79-90d6-124fb8cc3399 · outbound
This paper cites Blockchain- aided digital twin offloading mechanism in space-air-ground networks,.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization Blockchain- aided digital twin offloading mechanism in space-air-ground networks,
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.620495Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 4a7a6ec9-2bb3-4726-aed9-0759b39bf1ce · outbound
This paper cites A joint communication and computation framework for digital twin over wireless networks,.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization A joint communication and computation framework for digital twin over wireless networks,
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.606556Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 5fc1a886-aa9f-42bf-b850-71bdf7c544a4 · outbound
This paper cites A dynamic hierarchical framework for IoT-assisted digital twin synchronization in the metaverse,.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization A dynamic hierarchical framework for IoT-assisted digital twin synchronization in the metaverse,
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.593561Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation c69e1fc1-6696-4d0e-b379-ac88224021e9 · outbound
This paper cites Optimizing synchronization delay for digital twin over wireless networks,.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization Optimizing synchronization delay for digital twin over wireless networks,
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.580421Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 55251c47-ee06-496b-96f8-8fde3b846251 · outbound
This paper cites Uav- assisted digital twin synchronization with tiny machine learning-based semantic communications,.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization Uav- assisted digital twin synchronization with tiny machine learning-based semantic communications,
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.567036Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation c479ae7a-d3ac-422e-a64e-c48f7cb13dbc · outbound
This paper cites Data synchronization in vehicular digital twin network: A game theoretic approach,.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization Data synchronization in vehicular digital twin network: A game theoretic approach,
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.744869Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 8b01b690-da9e-4e10-aab3-d03d2dc7c1d8 · outbound
This paper cites Deep reinforcement learning for downlink scheduling in 5G and beyond networks: A review,.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization Deep reinforcement learning for downlink scheduling in 5G and beyond networks: A review,
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.553310Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation c41a75fc-dfb1-44df-b0b4-cf38ee52a4a1 · outbound
This paper cites Deep reinforcement learning for dynamic uplink/downlink resource allocation in high mobility 5G hetnet,.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization Deep reinforcement learning for dynamic uplink/downlink resource allocation in high mobility 5G hetnet,
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.539625Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 76800064-cab1-429b-8a1c-c9aed5e615bf · outbound
This paper cites Uplink power control framework based on reinforcement learning for 5G networks,.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization Uplink power control framework based on reinforcement learning for 5G networks,
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.524665Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation d215e0b8-459a-42af-8ea7-38b7b5bf00f3 · outbound
This paper cites Deep reinforcement learning for resource demand prediction and virtual function network migration in digital twin network,.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization Deep reinforcement learning for resource demand prediction and virtual function network migration in digital twin network,
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.510864Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation d4f74a4a-a55c-40bf-aad1-e6fb7f67d072 · outbound
This paper cites Adaptive edge association for wireless digital twin networks in 6G,.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization Adaptive edge association for wireless digital twin networks in 6G,
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.496900Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation b8ec18f6-5f33-4c05-b287-0a289200d858 · outbound
This paper cites Adaptive digital twin and multi- agent deep reinforcement learning for vehicular edge computing and networks,.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization Adaptive digital twin and multi- agent deep reinforcement learning for vehicular edge computing and networks,
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.483453Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 579a57bf-5bf1-4d27-b2c0-9b48fc77a25e · outbound
This paper cites Digital-twin- assisted task assignment in multi-uav systems: A deep reinforcement learning approach,.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization Digital-twin- assisted task assignment in multi-uav systems: A deep reinforcement learning approach,
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.469751Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 61e24d54-6ea0-4682-b7eb-97ac108f204e · outbound
This paper cites 3GPP TS 23.501: Sys- tem Architecture for the 5G System (5GS),.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization 3GPP TS 23.501: Sys- tem Architecture for the 5G System (5GS),
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.455366Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 4aa5d1f1-f561-492c-aee8-fa4fc64ed9b8 · outbound
This paper cites A general upper bound to evaluate packet error rate over quasi-static fading channels,.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization A general upper bound to evaluate packet error rate over quasi-static fading channels,
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.440901Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation b39a293e-af9d-4a4b-8f48-789832ca19e5 · outbound
This paper cites The logarithmic nature of qoe and the role of the weber-fechner law in QoE assessment,.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization The logarithmic nature of qoe and the role of the weber-fechner law in QoE assessment,
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.426449Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation cb8a5285-877d-4b3a-8bcc-4ca453cf44ee · outbound
This paper cites Multistate constraint multipath-assisted positioning and mismatch alleviation,.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization Multistate constraint multipath-assisted positioning and mismatch alleviation,
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.411320Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 0bdcfe22-93a2-4413-8462-37468c276a04 · outbound
This paper cites Altman, Constrained Markov decision processes.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization Altman, Constrained Markov decision processes
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.397062Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 9895103a-5b49-4962-b165-27e1c432aecb · outbound
This paper cites Performance optimization for digital internet-of-things twins over wireless networks,.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization Performance optimization for digital internet-of-things twins over wireless networks,
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.382896Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation a6493f11-cd71-40f8-a630-a775af76ae71 · outbound
This paper cites Toward enhanced reinforcement learning-based resource management via dig- ital twin: Opportunities, applications, and challenges,.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization Toward enhanced reinforcement learning-based resource management via dig- ital twin: Opportunities, applications, and challenges,
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.368710Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation e37cc7a5-09f5-448c-b436-1ae03ee72c1c · outbound
This paper cites Continual Reinforcement Learning with Multi-Timescale Replay.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization Continual Reinforcement Learning with Multi-Timescale Replay
Reference 36
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T20:37:04.123256Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e38fad77-df4c-4aef-baa5-1a414b832de5 · outbound
This paper cites Feasible Actor-Critic: Constrained Reinforcement Learning for Ensuring Statewise Safety.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization Feasible Actor-Critic: Constrained Reinforcement Learning for Ensuring Statewise Safety
Reference 37
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T20:37:04.127976Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2886e0ef-f333-4c0d-8bb9-a5c263072bac · outbound
This paper cites The age of incorrect in- formation: an enabler of semantics-empowered communication,.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization The age of incorrect in- formation: an enabler of semantics-empowered communication,
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.354418Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 809f38a2-ebd0-498c-b7ef-f3c5ad976829 · outbound
This paper cites Last-iterate convergent policy gradient primal-dual methods for constrained MDPs,.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization Last-iterate convergent policy gradient primal-dual methods for constrained MDPs,
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.338637Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation cd9dffde-501c-4e57-bcaa-b6a38bfb97ab · outbound
This paper cites Soft actor-critic: Off- policy maximum entropy deep reinforcement learning with a stochastic actor,.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization Soft actor-critic: Off- policy maximum entropy deep reinforcement learning with a stochastic actor,
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.322276Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 2204aa8f-4b50-4e1a-9707-4feab140b14f · outbound
This paper cites Soft Actor-Critic Algorithms and Applications.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization Soft Actor-Critic Algorithms and Applications
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T20:37:04.146276Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9e69c8a7-d665-4853-95ad-197e63b3fc1e · outbound
This paper cites Invariant Risk Minimization.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization Invariant Risk Minimization
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T20:37:04.151013Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 54752ef1-c0e3-4a52-a11a-a29b33144ac0 · outbound
This paper cites Semantic- aware remote state estimation in digital twin with minimizing age of incorrect information,.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization Semantic- aware remote state estimation in digital twin with minimizing age of incorrect information,
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.307673Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 5110d33d-8c6f-402f-9033-c270dd3d375b · outbound
This paper cites Federated learning based audio semantic communication over wireless networks,.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization Federated learning based audio semantic communication over wireless networks,
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.292875Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 78698985-bdec-4229-af6d-66123d58eb28 · outbound
This paper cites Intel berkeley research lab sensor data,.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization Intel berkeley research lab sensor data,
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:37:04.278129Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 47cdc717-ceee-4ffa-ae41-31b05abf341b · outbound
This paper cites Indoor received signal strength data generated from ray- tracing,.
Continual Reinforcement Learning for Digital Twin Synchronization Optimization Indoor received signal strength data generated from ray- tracing,
Reference 46
- Resolution
- malformed identifier
- raw_fallback, observed 2026-08-10T20:37:04.263266Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Pith citing papers
No inbound Pith citation observations are available.