Paper Citation Record · LEDGER

GenAI-Enhanced Digital Twins for Predictive Interference Management in Ultra-Dense Networks

As of 9 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2607.08141.

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

pith.paper-citation-record.v1
2607.08141 v1

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-10T12:25:58.741229Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

16 of 16 outbound references displayed

verified exact1
verified fuzzy15
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 028219a7-d763-409d-a630-91943f6deffa · outbound

This paper cites A survey of beam management for mmWave and THz communications towards 6G,.

GenAI-Enhanced Digital Twins for Predictive Interference Management in Ultra-Dense Networks A survey of beam management for mmWave and THz communications towards 6G,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:27:04.280240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 10632a52-9cf5-4e1d-be00-ffcf34f1aef4 · outbound

This paper cites Dynamic THz backhaul for 6G local area networks: Architecture, analysis, challenges and future directions,.

GenAI-Enhanced Digital Twins for Predictive Interference Management in Ultra-Dense Networks Dynamic THz backhaul for 6G local area networks: Architecture, analysis, challenges and future directions,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:27:04.278503Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 62016db1-8ebb-4e9c-aae9-733f735881bb · outbound

This paper cites From 5G to 6G networks: A survey on AI-based jamming and interference detection and mitigation,.

GenAI-Enhanced Digital Twins for Predictive Interference Management in Ultra-Dense Networks From 5G to 6G networks: A survey on AI-based jamming and interference detection and mitigation,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:27:04.271215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3da4eb7c-5c6e-46c7-8261-14153dd251f2 · outbound

This paper cites A digital twin network approach for 6G wireless network autonomy,.

GenAI-Enhanced Digital Twins for Predictive Interference Management in Ultra-Dense Networks A digital twin network approach for 6G wireless network autonomy,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:27:04.281941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 77a5fef6-1554-4d46-b22c-ad4eff23eda9 · outbound

This paper cites Digital twin networks for sustainable in-network computing in future 6G networks,.

GenAI-Enhanced Digital Twins for Predictive Interference Management in Ultra-Dense Networks Digital twin networks for sustainable in-network computing in future 6G networks,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:27:04.257572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 63f19738-6516-4f7f-a3bf-54a473bf2d7b · outbound

This paper cites Wireless network digital twin for 6G: Generative AI as a key enabler,.

GenAI-Enhanced Digital Twins for Predictive Interference Management in Ultra-Dense Networks Wireless network digital twin for 6G: Generative AI as a key enabler,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:27:04.276507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation dbf22f91-2083-4646-b400-92b9e80becdf · outbound

This paper cites Integrating generative AI with network digital twin for 6G: An edge–cloud collaborative approach,.

GenAI-Enhanced Digital Twins for Predictive Interference Management in Ultra-Dense Networks Integrating generative AI with network digital twin for 6G: An edge–cloud collaborative approach,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:27:04.273071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7d45c017-3aa8-42c1-adf9-510a2380c4c1 · outbound

This paper cites Generative AI-driven digital twin for mobile networks,.

GenAI-Enhanced Digital Twins for Predictive Interference Management in Ultra-Dense Networks Generative AI-driven digital twin for mobile networks,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:27:04.261631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7ce727ef-8d46-4c81-90fa-c6585e5a0bbf · outbound

This paper cites Enhancing open RAN digital twin through power consumption measurement,.

GenAI-Enhanced Digital Twins for Predictive Interference Management in Ultra-Dense Networks Enhancing open RAN digital twin through power consumption measurement,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:27:04.269125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d7142eef-9e9d-4bc7-b567-0a186787b44a · outbound

This paper cites Large generative model-enabled digital twin for 6G networks,.

GenAI-Enhanced Digital Twins for Predictive Interference Management in Ultra-Dense Networks Large generative model-enabled digital twin for 6G networks,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:27:04.283671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation cf1b057a-bb08-4701-9dfa-d333a329004b · outbound

This paper cites Gen-TWIN: Generative-AI-enabled digital twin for open radio access networks,.

GenAI-Enhanced Digital Twins for Predictive Interference Management in Ultra-Dense Networks Gen-TWIN: Generative-AI-enabled digital twin for open radio access networks,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:27:04.267371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 52d86bf6-7e18-41cc-93f2-a490b4873aca · outbound

This paper cites Digital twin-based reinforcement learning for beam selection in cell-free networks,.

GenAI-Enhanced Digital Twins for Predictive Interference Management in Ultra-Dense Networks Digital twin-based reinforcement learning for beam selection in cell-free networks,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:27:04.274730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 727f15f7-92fc-4dcd-9391-bedfb7918910 · outbound

This paper cites A generative AI-enhanced digital twin framework for heterogeneous networks and smart environments,.

GenAI-Enhanced Digital Twins for Predictive Interference Management in Ultra-Dense Networks A generative AI-enhanced digital twin framework for heterogeneous networks and smart environments,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:27:04.265472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d287f114-400c-43f1-8067-1b068a4c5029 · outbound

This paper cites Sionna: An Open-Source Library for Next-Generation Physical Layer Research.

GenAI-Enhanced Digital Twins for Predictive Interference Management in Ultra-Dense Networks Sionna: An Open-Source Library for Next-Generation Physical Layer Research

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-07-10T12:27:04.169411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a214b785-0130-44a8-a11b-b390c1e78526 · outbound

This paper cites Image-to-image translation with conditional adversarial networks,.

GenAI-Enhanced Digital Twins for Predictive Interference Management in Ultra-Dense Networks Image-to-image translation with conditional adversarial networks,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:27:04.263492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9445ce27-3012-4cbf-8e03-29b3206702d7 · outbound

This paper cites Improved training of Wasserstein GANs,.

GenAI-Enhanced Digital Twins for Predictive Interference Management in Ultra-Dense Networks Improved training of Wasserstein GANs,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:27:04.259733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Pith citing papers

No inbound Pith citation observations are available.