Paper Citation Record · LEDGER

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management

As of 15 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 3 inbound Pith citation observations for arXiv:2501.12991.

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

pith.paper-citation-record.v1
2501.12991 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T16:38:26.733680Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T15:55:04.341082Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-09T15:55:04.398895Z

Reference resolution

40 of 40 outbound references displayed

verified exact1
verified fuzzy23
unresolved16
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7d71513c-9f5f-4a2a-93a2-b3435fb52707 · outbound

This paper cites Applications of deep reinforcement learning in communications and networking: A survey,.

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management Applications of deep reinforcement learning in communications and networking: A survey,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-10T16:38:26.377434Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1fcb869b-748c-4833-8e12-1408e6dd4db3 · outbound

This paper cites Machine type communications: key drivers and enablers towards the 6G era,.

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management Machine type communications: key drivers and enablers towards the 6G era,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:38:28.353585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f89b911a-4939-477b-9955-242340c90f7e · outbound

This paper cites Machine learning for large-scale optimization in 6G wireless networks,.

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management Machine learning for large-scale optimization in 6G wireless networks,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-10T16:38:26.387098Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b169aff0-50b1-4008-b570-6194553607b9 · outbound

This paper cites Traffic prediction and fast uplink for hidden markov IoT models,.

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management Traffic prediction and fast uplink for hidden markov IoT models,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-10T16:38:26.391573Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7bdf73bb-4cb6-4eac-8c3e-31948bd53963 · outbound

This paper cites ITLinQ+: An improved spectrum sharing mech- anism for device-to-device communications,.

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management ITLinQ+: An improved spectrum sharing mech- anism for device-to-device communications,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:38:28.307166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0603d526-e60b-4646-b84b-29890a4a6360 · outbound

This paper cites Binary power control for sum rate maximization over multiple interfering links,.

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management Binary power control for sum rate maximization over multiple interfering links,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:38:28.264891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 87163d71-2dde-4d97-bbda-a357717ebbea · outbound

This paper cites Game-theoretic resource allocation methods for device-to-device communication,.

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management Game-theoretic resource allocation methods for device-to-device communication,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:38:28.168993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 43973fb1-4fe0-4d83-8a5f-077d92220f0d · outbound

This paper cites Reinforcement learning for radio resource management in RAN slicing: A survey,.

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management Reinforcement learning for radio resource management in RAN slicing: A survey,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:38:27.995236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 735ef8f1-f2dd-4537-8266-e26a3b4cd0a6 · outbound

This paper cites Human-level control through deep reinforcement learning,.

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management Human-level control through deep reinforcement learning,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:38:27.889435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e01f4e44-e7f2-4d5d-af5c-3269828ce5ea · outbound

This paper cites Distributed learning methodologies for massive machine type commu- nication,.

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management Distributed learning methodologies for massive machine type commu- nication,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-10T16:38:26.417654Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84ac731c-bba5-457c-8881-d00ac52865a6 · outbound

This paper cites A review of cooperative multi-agent deep reinforcement learning,.

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management A review of cooperative multi-agent deep reinforcement learning,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T16:38:26.422116Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d78e7986-f0c9-45e9-ab32-ccbddf6842f3 · outbound

This paper cites Multiagent cooperation and competition with deep reinforcement learning,.

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management Multiagent cooperation and competition with deep reinforcement learning,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:38:27.778506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 66b0eda9-c64a-4673-a906-3c5990328021 · outbound

This paper cites Traffic learning and proactive UA V trajectory planning for data uplink in markovian IoT models,.

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management Traffic learning and proactive UA V trajectory planning for data uplink in markovian IoT models,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T16:38:26.430814Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 716a8365-1daa-4776-be8b-39873a992dac · outbound

This paper cites an unresolved cited work.

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management Unresolved cited work

Reference 14

Resolution: unresolved; raw_fallback, observed 2026-08-10T16:38:27.746843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5b0a152c-e1be-4636-aeea-bc7d40772eb1 · outbound

This paper cites Value-Decomposition Networks For Cooperative Multi-Agent Learning.

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management Value-Decomposition Networks For Cooperative Multi-Agent Learning

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T16:38:26.438685Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f004739c-02cf-4384-bba4-f63558092690 · outbound

This paper cites Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems.

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-10T16:38:26.443158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 869719da-66ed-4fbc-964b-b6de49ad4e56 · outbound

This paper cites Offline Reinforcement Learning with Implicit Q-Learning.

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management Offline Reinforcement Learning with Implicit Q-Learning

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-10T16:38:26.447226Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c9c98b66-7cc4-49e5-8643-b6b6fb8a400d · outbound

This paper cites Trust region policy optimization,.

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management Trust region policy optimization,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T16:38:26.451361Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2f4a169e-6b7d-499d-966b-578772424190 · outbound

This paper cites Conservative Q-learning for offline reinforcement learning,.

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management Conservative Q-learning for offline reinforcement learning,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:38:27.704739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 805f3ed8-0c1e-491a-af3a-365dcf7b8bda · outbound

This paper cites Self- organization in small cell networks: A reinforcement learning approach,.

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management Self- organization in small cell networks: A reinforcement learning approach,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-10T16:38:26.457917Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dfce22b9-4928-42d3-a04a-36253c9ef5f3 · outbound

This paper cites Intelligent power control for spectrum sharing in cognitive radios: A deep rein- forcement learning approach,.

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management Intelligent power control for spectrum sharing in cognitive radios: A deep rein- forcement learning approach,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T16:38:26.462158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 122452db-342a-4b00-ada6-9222e3c3aaea · outbound

This paper cites Multi-UA V path learning for age and power optimization in IoT with UA V battery recharge,.

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management Multi-UA V path learning for age and power optimization in IoT with UA V battery recharge,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-10T16:38:26.466094Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c93a2828-5430-4f29-b302-506fc9c5988f · outbound

This paper cites GAN-Powered Deep Distributional Reinforcement Learning for Resource Management in Network Slicing,.

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management GAN-Powered Deep Distributional Reinforcement Learning for Resource Management in Network Slicing,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:38:27.574737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation af79347b-0df3-4cde-bbca-863a9736d2de · outbound

This paper cites Learning resilient radio resource management policies with graph neural networks,.

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management Learning resilient radio resource management policies with graph neural networks,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:38:27.527007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5ff51be5-31b4-4171-89b2-2190470d0289 · outbound

This paper cites Age minimization in massive IoT via UA V swarm: A multi-agent reinforcement learning approach,.

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management Age minimization in massive IoT via UA V swarm: A multi-agent reinforcement learning approach,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:38:27.488983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2564065d-ce49-458e-899d-c1f0ab8a3c46 · outbound

This paper cites Resource management in wireless networks via multi-agent deep reinforcement learning,.

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management Resource management in wireless networks via multi-agent deep reinforcement learning,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:38:27.434744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3cc94fe7-2fb0-46ee-856f-823605af0e3f · outbound

This paper cites Multi-agent deep reinforcement learning for dynamic power allocation in wireless networks,.

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management Multi-agent deep reinforcement learning for dynamic power allocation in wireless networks,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-10T16:38:26.573908Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d2a53a4-26ed-458e-b9b5-7d80d3893d86 · outbound

This paper cites Multi-agent deep reinforcement learning for distributed resource management in wirelessly powered communication networks,.

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management Multi-agent deep reinforcement learning for distributed resource management in wirelessly powered communication networks,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:38:27.316562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d1711627-08c0-4e2c-ac39-873f11bc8bcd · outbound

This paper cites Multi-agent reinforcement learning for dynamic resource management in 6G in-X subnetworks,.

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management Multi-agent reinforcement learning for dynamic resource management in 6G in-X subnetworks,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:38:27.261959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 941997f2-b1b5-4268-8480-bd88ac62d783 · outbound

This paper cites Conservative and Risk-Aware Offline Multi-Agent Reinforcement Learning.

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management Conservative and Risk-Aware Offline Multi-Agent Reinforcement Learning

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-08-10T16:38:26.792615Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 23877ae2-2859-4cca-9cb2-3ebf5db9a51e · outbound

This paper cites Offline reinforcement learning for wireless network optimization with mixture datasets,.

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management Offline reinforcement learning for wireless network optimization with mixture datasets,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:38:27.243284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8a07c1c9-3bfd-45a8-bfec-462e9db6398f · outbound

This paper cites Offline and Distributional Reinforcement Learning for Radio Resource Management.

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management Offline and Distributional Reinforcement Learning for Radio Resource Management

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-10T16:38:26.703308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 30ffdfdd-7217-40b3-ace4-9eb4ca16137e · outbound

This paper cites Offline pre-trained multi-agent decision transformer,.

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management Offline pre-trained multi-agent decision transformer,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:38:27.206189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 139ee972-80a6-4d0a-84da-5bc13e8c7d67 · outbound

This paper cites Simulation assumptions and parameters for FDD HeNB RF requirements,.

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management Simulation assumptions and parameters for FDD HeNB RF requirements,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:38:27.113493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 90e2dd4c-342a-47c4-b5b4-1eccae466435 · outbound

This paper cites NR; physical layer measurements,.

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management NR; physical layer measurements,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:38:27.065394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a53bb287-3bb2-45dd-a55f-1afc03342f70 · outbound

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

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:38:27.005362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5eb5ba51-366b-4228-9603-4174863e201d · outbound

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

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:38:26.902181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 78170cad-effe-4c74-834c-8afe0d12f9ef · outbound

This paper cites Value-decomposition multi-agent actor- critics,.

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management Value-decomposition multi-agent actor- critics,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:38:26.871767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b16994bf-91fe-48ee-a830-8f0f3ae11f3e · outbound

This paper cites Off-policy deep reinforcement learning without exploration,.

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management Off-policy deep reinforcement learning without exploration,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:38:26.857112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0ebd5816-83ba-4ba1-a3a4-e64ec924adce · outbound

This paper cites ITLinQ: A new approach for spectrum sharing in device-to-device communication systems,.

An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management ITLinQ: A new approach for spectrum sharing in device-to-device communication systems,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:38:26.843606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Pith citing papers

Observation 9f306572-e2e7-414a-83fb-9e47fd72be58 · inbound

Resilient UAV Trajectory Planning via Few-Shot Meta-Offline Reinforcement Learning cites this paper.

Resilient UAV Trajectory Planning via Few-Shot Meta-Offline Reinforcement Learning An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management

Reference 36

Resolution: verified exact; local_arxiv, observed 2026-08-09T15:55:04.404438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1d288dbb-6b10-4364-a3b6-13fe170d96bb · inbound

Federated Multi-Agent Reinforcement Learning for Privacy-Preserving and Energy-Aware Resource Management in 6G Edge Networks cites this paper.

Federated Multi-Agent Reinforcement Learning for Privacy-Preserving and Energy-Aware Resource Management in 6G Edge Networks An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-04T18:09:30.327529Z

Source-reported events for the cited work

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Observation 9433e9d2-a1c2-42cf-9fbd-a97138cf5e5a · inbound

DRL-Based Spectrum Sharing for RIS-Aided Local High-Quality Wireless Networks cites this paper.

DRL-Based Spectrum Sharing for RIS-Aided Local High-Quality Wireless Networks An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-02T17:28:25.473170Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.