Paper Citation Record · LEDGER

Mobile Network Control with a World Model

As of 9 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2607.17747.

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

pith.paper-citation-record.v1
2607.17747 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T17:08:46.651865Z

measured 33 of 33 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

33 of 33 outbound references displayed

verified exact0
verified fuzzy0
unresolved33
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malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 07e34bb6-f31f-4054-a2e7-535dbc94627f · outbound

This paper cites A survey on sleep mode techniques for ultra-dense networks in 5g and beyond,.

Mobile Network Control with a World Model A survey on sleep mode techniques for ultra-dense networks in 5g and beyond,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:42.685431Z

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Unavailable: canonical work link unavailable.

Observation a01384cc-5f8a-4926-b0f0-efd11c6a7621 · outbound

This paper cites Multi-agent reinforcement learning with common policy for antenna tilt optimization,.

Mobile Network Control with a World Model Multi-agent reinforcement learning with common policy for antenna tilt optimization,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:42.813923Z

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Observation b1e8a7f7-f286-4797-9a90-2e8814728eea · outbound

This paper cites Drag: Deep reinforcement learning based base station activation in heterogeneous networks,.

Mobile Network Control with a World Model Drag: Deep reinforcement learning based base station activation in heterogeneous networks,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:42.988658Z

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Observation db610222-0079-4a7c-ac84-2d681ea82cf9 · outbound

This paper cites Telenor: Autonomous AI agent with Ericsson,.

Mobile Network Control with a World Model Telenor: Autonomous AI agent with Ericsson,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:43.190499Z

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Observation a819aa71-6449-480b-b4d6-1e29e50c31e2 · outbound

This paper cites Deep rein- forcement learning for cell on/off energy saving on wireless networks,.

Mobile Network Control with a World Model Deep rein- forcement learning for cell on/off energy saving on wireless networks,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:43.316057Z

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Observation d6969f65-a46c-4c85-8079-02a796531350 · outbound

This paper cites Deep rein- forcement learning in a handful of trials using probabilistic dynamics models,.

Mobile Network Control with a World Model Deep rein- forcement learning in a handful of trials using probabilistic dynamics models,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:43.426295Z

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Observation 743d2412-8a9b-4afb-9ba8-b0e241eeae42 · outbound

This paper cites Mastering Diverse Domains through World Models.

Mobile Network Control with a World Model Mastering Diverse Domains through World Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:43.523644Z

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Observation c8fc746f-d28d-4bf6-a399-35144681667b · outbound

This paper cites A survey on 5g radio access network energy efficiency: Massive mimo, lean carrier design, sleep modes, and machine learning,.

Mobile Network Control with a World Model A survey on 5g radio access network energy efficiency: Massive mimo, lean carrier design, sleep modes, and machine learning,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:43.642764Z

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Observation a69773bb-512f-422f-a9dd-ca11c994398a · outbound

This paper cites Traffic-aware advanced sleep modes management in 5g networks,.

Mobile Network Control with a World Model Traffic-aware advanced sleep modes management in 5g networks,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:43.747995Z

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Observation 1153d9dc-cd4d-4ade-ac3d-f881fee2f2f1 · outbound

This paper cites Downlink power control in dense 5g radio access networks through deep reinforcement learning,.

Mobile Network Control with a World Model Downlink power control in dense 5g radio access networks through deep reinforcement learning,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:43.858355Z

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Observation b594c9fd-3d09-44d9-a977-ec6a9d1e9e92 · outbound

This paper cites Energy saving in 6g o-ran using dqn-based xapp,.

Mobile Network Control with a World Model Energy saving in 6g o-ran using dqn-based xapp,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:43.940682Z

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Observation de96bd7e-7db6-4051-bf3a-61d879fc13a2 · outbound

This paper cites Energy efficient sleep mode strategies for communication and computing devices in cellular networks with edge computing,.

Mobile Network Control with a World Model Energy efficient sleep mode strategies for communication and computing devices in cellular networks with edge computing,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:44.058088Z

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Observation 24309e3b-631a-44e1-8715-0cd46fd136b9 · outbound

This paper cites Energy optimization with multi-sleeping control in 5g heterogeneous networks using reinforcement learning,.

Mobile Network Control with a World Model Energy optimization with multi-sleeping control in 5g heterogeneous networks using reinforcement learning,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:44.162269Z

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Observation c91369b3-f5aa-4b5a-a974-2a1a03522746 · outbound

This paper cites An efficient energy saving scheme using reinforcement learning for 5g and beyond in h-cran,.

Mobile Network Control with a World Model An efficient energy saving scheme using reinforcement learning for 5g and beyond in h-cran,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:44.253641Z

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Observation 643b791a-94cb-44fe-95b6-2a57c49cd679 · outbound

This paper cites Design and evaluation of deep reinforcement learning for energy saving in open ran,.

Mobile Network Control with a World Model Design and evaluation of deep reinforcement learning for energy saving in open ran,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:44.368171Z

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Observation 3c149ec8-0cb7-4311-8854-49cf6b4ac3c7 · outbound

This paper cites Model-based reinforcement learning for energy efficiency optimization in small-cell networks,.

Mobile Network Control with a World Model Model-based reinforcement learning for energy efficiency optimization in small-cell networks,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:44.457681Z

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Observation 0c24003c-17e3-4fcd-8dcd-9f69675a14c3 · outbound

This paper cites Data-driven cell zooming for large-scale mobile networks,.

Mobile Network Control with a World Model Data-driven cell zooming for large-scale mobile networks,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:44.626957Z

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Observation cead4aaa-7e7c-4670-8a03-1cffc441d5bb · outbound

This paper cites A coalitional model predictive control approach for heterogeneous cellular networks,.

Mobile Network Control with a World Model A coalitional model predictive control approach for heterogeneous cellular networks,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:44.693807Z

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Observation 456f2fc7-aa0f-4515-a6e0-798c06741f66 · outbound

This paper cites Application-level service assurance with 5g ran slicing,.

Mobile Network Control with a World Model Application-level service assurance with 5g ran slicing,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:44.858219Z

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Observation 8d522258-52f7-4de1-b594-0cfa8b9f4411 · outbound

This paper cites Greener ran operation through machine learning,.

Mobile Network Control with a World Model Greener ran operation through machine learning,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:45.004829Z

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Observation d8dd22b0-1710-4f64-acc3-2c382a756745 · outbound

This paper cites A ml-based resource allocation scheme for energy optimization in 5g nr,.

Mobile Network Control with a World Model A ml-based resource allocation scheme for energy optimization in 5g nr,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:45.147514Z

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Observation 7b90a3fe-6e5d-42d2-b811-8d7ee865fdb6 · outbound

This paper cites World Models.

Mobile Network Control with a World Model World Models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:45.254286Z

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Observation 9f5a0ac7-0a98-4999-9cd9-cb770f48b73c · outbound

This paper cites TD-MPC2: Scalable, Robust World Models for Continuous Control.

Mobile Network Control with a World Model TD-MPC2: Scalable, Robust World Models for Continuous Control

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:45.367611Z

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Observation f66561f2-74ad-4dbf-84f3-88006f042106 · outbound

This paper cites Potential solutions for energy saving for E-UTRAN,.

Mobile Network Control with a World Model Potential solutions for energy saving for E-UTRAN,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:45.449071Z

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Observation 1191d695-0b58-4762-91bb-82171e5f384d · outbound

This paper cites An Axiomatic Assessment of Entropy- and Variance-based Uncertainty Quantification in Regression.

Mobile Network Control with a World Model An Axiomatic Assessment of Entropy- and Variance-based Uncertainty Quantification in Regression

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:45.548898Z

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Observation b411c462-578a-47c8-8edd-e3c307acb9bb · outbound

This paper cites Receding horizon control,.

Mobile Network Control with a World Model Receding horizon control,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:45.711845Z

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Observation de5bca08-f336-40ac-8181-8143f318ef66 · outbound

This paper cites an unresolved cited work.

Mobile Network Control with a World Model Unresolved cited work

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:45.827900Z

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Observation bdd35f3f-d510-41ab-929f-bb195a38db07 · outbound

This paper cites A set of propagation models for site-specific predictions,.

Mobile Network Control with a World Model A set of propagation models for site-specific predictions,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:45.948886Z

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Observation e851567e-4a64-460d-aae3-4a95bf7c5633 · outbound

This paper cites Spatial modeling of the traffic density in cellular networks,.

Mobile Network Control with a World Model Spatial modeling of the traffic density in cellular networks,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:46.205767Z

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Observation 4631eb8a-0f83-471e-b370-251ff3b8addb · outbound

This paper cites Soft actor-critic: Off- policy maximum entropy deep reinforcement learning with a stochastic actor,.

Mobile Network Control with a World Model Soft actor-critic: Off- policy maximum entropy deep reinforcement learning with a stochastic actor,

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:46.342827Z

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Observation abc17924-6b1b-4460-ab19-e7713657e713 · outbound

This paper cites A learning algorithm for continually running fully recurrent neural networks,.

Mobile Network Control with a World Model A learning algorithm for continually running fully recurrent neural networks,

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:46.459885Z

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Observation b49d28be-c9f9-485f-8a1e-92aeed6280b9 · outbound

This paper cites Reversible instance normalization for accurate time-series forecasting against distribution shift,.

Mobile Network Control with a World Model Reversible instance normalization for accurate time-series forecasting against distribution shift,

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:46.562331Z

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Observation 16b1a242-a70e-465d-bfb8-fa3df72234c2 · outbound

This paper cites Layer Normalization.

Mobile Network Control with a World Model Layer Normalization

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:46.651865Z

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Pith citing papers

No inbound Pith citation observations are available.