Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Large Vision Model-Enhanced Digital Twin with Deep Reinforcement Learning for User Association and Load Balancing in Dynamic Wireless Networks
As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2410.07611.
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 2026-08-23T06:30:58.430688+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T15:39:59.137414Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T05:35:42.277378Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 4db860d9-2723-4791-8955-a2efbd19ff70 · inbound
Learning to Gridize: Segment Physical World by Wireless Communication Channel cites this paper.
Learning to Gridize: Segment Physical World by Wireless Communication Channel Large Vision Model-Enhanced Digital Twin with Deep Reinforcement Learning for User Association and Load Balancing in Dynamic Wireless Networks
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T15:39:59.137414Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9118b48a-9ae3-4251-bef8-089eaa200e2d · inbound
Censored Sampling for Topology Design: Guiding Diffusion with Human Preferences cites this paper.
Censored Sampling for Topology Design: Guiding Diffusion with Human Preferences Large Vision Model-Enhanced Digital Twin with Deep Reinforcement Learning for User Association and Load Balancing in Dynamic Wireless Networks
Reference 218
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T05:35:42.370865Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 3c1ec748-8956-415a-bc34-00c246122626 · inbound
Large Language Models for Next-Generation Wireless Network Management: A Survey and Tutorial cites this paper.
Large Language Models for Next-Generation Wireless Network Management: A Survey and Tutorial Large Vision Model-Enhanced Digital Twin with Deep Reinforcement Learning for User Association and Load Balancing in Dynamic Wireless Networks
Reference 70
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T04:50:31.707007Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a8c3bb68-cf83-4ae7-bd18-551fc823cb91 · inbound
Toward Trustworthy Digital Twins in AI Agent-based Wireless Network Optimization: Challenges, Solutions, and Opportunities cites this paper.
Toward Trustworthy Digital Twins in AI Agent-based Wireless Network Optimization: Challenges, Solutions, and Opportunities Large Vision Model-Enhanced Digital Twin with Deep Reinforcement Learning for User Association and Load Balancing in Dynamic Wireless Networks
Reference 2024
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T20:26:58.178718Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.