Paper Citation Record · LEDGER

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G

As of 21 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2505.01841.

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

pith.paper-citation-record.v1
2505.01841 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:12:56.212310Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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

43 of 43 outbound references displayed

verified exact0
verified fuzzy27
unresolved16
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e936964f-0f1e-4670-9602-b25e433c054f · outbound

This paper cites Management and Orchestration; Intent Driven Man- agement Services for Mobile Networks,.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G Management and Orchestration; Intent Driven Man- agement Services for Mobile Networks,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:12:56.841856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 59afe1c8-33c9-454a-80d5-e843a64ae483 · outbound

This paper cites Towards Intent-Based Network Management: Large Language Models for Intent Extraction in 5G Core Networks,.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G Towards Intent-Based Network Management: Large Language Models for Intent Extraction in 5G Core Networks,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:12:56.828116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 913b0edd-b48a-4b06-bcc7-2b46a361e775 · outbound

This paper cites SMART Intent-Driven Network Management,.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G SMART Intent-Driven Network Management,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:12:56.814977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 595a2ae7-8b75-4afb-900b-69408d64188d · outbound

This paper cites LLM-Based Policy Generation for Intent-Based Management of Applications,.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G LLM-Based Policy Generation for Intent-Based Management of Applications,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:12:56.801846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9bbeb8e3-e55c-42aa-8e3d-8dedfe53e14f · outbound

This paper cites NLP Powered Intent Based Network Management for Private 5G Networks,.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G NLP Powered Intent Based Network Management for Private 5G Networks,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:12:56.787382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5f697dee-447f-409a-a042-d8de123af6b5 · outbound

This paper cites Network Meets ChatGPT: Intent Autonomous Man- agement, Control and Operation,.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G Network Meets ChatGPT: Intent Autonomous Man- agement, Control and Operation,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:12:56.773550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 62e6190e-83f5-4eb2-bf4f-fd4e78e6253d · outbound

This paper cites ColO- RAN: Developing Machine Learning-Based xApps for Open RAN Closed-Loop Control on Programmable Experimental Platforms,.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G ColO- RAN: Developing Machine Learning-Based xApps for Open RAN Closed-Loop Control on Programmable Experimental Platforms,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:12:56.758605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d6fbd46c-73d9-437d-9edb-08c446175f1b · outbound

This paper cites Intent-driven Intelligent Control and Orchestration in O-RAN Via Hierarchical Reinforcement Learning,.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G Intent-driven Intelligent Control and Orchestration in O-RAN Via Hierarchical Reinforcement Learning,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:12:56.744249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8452af1f-b288-4291-b448-37f44b4fcb0e · outbound

This paper cites LLM-Based Intent Processing and Network Optimization Using Attention-Based Hierarchical Reinforcement Learning.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G LLM-Based Intent Processing and Network Optimization Using Attention-Based Hierarchical Reinforcement Learning

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-16T04:12:56.048533Z

Source-reported events for the cited work

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Observation f0d4354d-32bb-4523-83b8-9c5fea7dda0e · outbound

This paper cites Attention Is All You Need.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G Attention Is All You Need

Reference 10

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b1e9bf01-f337-40bb-a351-b3d901f46468 · outbound

This paper cites QLoRA: Efficient Finetuning of Quantized LLMs.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G QLoRA: Efficient Finetuning of Quantized LLMs

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-16T04:12:56.058098Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c9443455-4d14-4f0d-8200-c8f148768e4e · outbound

This paper cites Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-16T04:12:56.067525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 331febfd-83f2-46fc-9637-3cb1ec2cb863 · outbound

This paper cites Decision Transformer: Reinforcement Learning via Sequence Modeling.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G Decision Transformer: Reinforcement Learning via Sequence Modeling

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-16T04:12:56.072139Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c66715f9-65f2-4e83-9b8c-df4e7cffdcf8 · outbound

This paper cites FeUdal Networks for Hierarchical Reinforcement Learning.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G FeUdal Networks for Hierarchical Reinforcement Learning

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-16T04:12:56.077172Z

Source-reported events for the cited work

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Observation 720888df-414a-4ac9-a90b-ad048c90a801 · outbound

This paper cites Intent Assurance using LLMs guided by Intent Drift,.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G Intent Assurance using LLMs guided by Intent Drift,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:12:56.730799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3a52eb91-555d-4be0-83a7-04866d84533c · outbound

This paper cites OrchestRAN: Orches- trating Network Intelligence in the Open RAN,.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G OrchestRAN: Orches- trating Network Intelligence in the Open RAN,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:12:56.717091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 62c525aa-c356-4eab-9d28-d849ee4afdd3 · outbound

This paper cites Op- timizing Energy Saving for Wireless Networks Via Offline Decision Transformer,.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G Op- timizing Energy Saving for Wireless Networks Via Offline Decision Transformer,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:12:56.702299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e36dcb0c-c879-48c2-9e9d-7546ca5a2476 · outbound

This paper cites Decision Transformers for Wireless Communications: A New Paradigm of Resource Management.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G Decision Transformers for Wireless Communications: A New Paradigm of Resource Management

Reference 19

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Source-reported events for the cited work

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Observation df4c5e70-3e1c-48d2-9094-a46f2605c619 · outbound

This paper cites Study on channel model for frequencies from 0.5 to 100 ghz,.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G Study on channel model for frequencies from 0.5 to 100 ghz,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:12:56.688741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9322968e-8670-4082-870d-9b5e8eeb72a9 · outbound

This paper cites Deep Learning Predictive Band Switching in Wireless Networks,.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G Deep Learning Predictive Band Switching in Wireless Networks,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:12:56.675344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7f29ec94-5f24-41b5-9ecb-3724e34f41c8 · outbound

This paper cites Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-16T04:12:56.108147Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 700f1749-b27b-445f-9c5a-0f56af6e975c · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G LoRA: Low-Rank Adaptation of Large Language Models

Reference 23

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 36870d0a-da2e-4229-9327-b44466665569 · outbound

This paper cites Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-16T04:12:56.116809Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c07011b-18f0-4f40-9c7e-917a30c37b69 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G LLaMA: Open and Efficient Foundation Language Models

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-16T04:12:56.120960Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0fa2c8e4-932e-405c-ab0e-b0c050601e0e · outbound

This paper cites Transformer-Based Wireless Traffic Prediction and Network Optimization in O-RAN.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G Transformer-Based Wireless Traffic Prediction and Network Optimization in O-RAN

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-16T04:12:56.125907Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d19fc04-de27-4b42-9948-7b460535dd07 · outbound

This paper cites Traffic Steering for 5G Multi-RAT Deployments Using Deep Reinforcement Learning,.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G Traffic Steering for 5G Multi-RAT Deployments Using Deep Reinforcement Learning,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:12:56.662025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 36f862b0-bafb-46f1-83f2-b186f6a3b8ff · outbound

This paper cites Cooperative Hierarchical Deep Reinforcement Learning Based Joint Sleep and Power Control in RIS-Aided Energy-Efficient RAN,.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G Cooperative Hierarchical Deep Reinforcement Learning Based Joint Sleep and Power Control in RIS-Aided Energy-Efficient RAN,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:12:56.648345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0ed818e6-fb7b-4334-a8c5-1255152627be · outbound

This paper cites Team Learning-Based Resource Allocation for Open Radio Access Network (O-RAN),.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G Team Learning-Based Resource Allocation for Open Radio Access Network (O-RAN),

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:12:56.633899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 103acacb-8835-487b-a8cc-12d7f879d1ed · outbound

This paper cites Deep Reinforcement Learning for 5G Networks: Joint Beamforming, Power Control, and Interference Coordination,.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G Deep Reinforcement Learning for 5G Networks: Joint Beamforming, Power Control, and Interference Coordination,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:12:56.620281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 79bcf6f1-ba12-4e12-895e-448c6a429b5e · outbound

This paper cites Handover Decision Making for Dense HetNets: A Reinforcement Learning Approach,.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G Handover Decision Making for Dense HetNets: A Reinforcement Learning Approach,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:12:56.604964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a3ea49a4-dbdf-4b88-b073-45ab5f1c3111 · outbound

This paper cites A Survey on 5G Usage Scenarios and Traffic Models,.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G A Survey on 5G Usage Scenarios and Traffic Models,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:12:56.590639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation faadc636-119f-41d2-86b4-7d5b1b50b553 · outbound

This paper cites Which Statistical Distribution Best Characterizes Modern Cellular Traffic and What Factors Could Predict Its Spatiotemporal Variability?.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G Which Statistical Distribution Best Characterizes Modern Cellular Traffic and What Factors Could Predict Its Spatiotemporal Variability?

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:12:56.576748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d4ce92a3-f9cb-4227-82da-920c71471ac6 · outbound

This paper cites AI-Enabled Radio Resource Allo- cation in 5G for URLLC and eMBB Users,.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G AI-Enabled Radio Resource Allo- cation in 5G for URLLC and eMBB Users,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:12:56.562179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3cec1752-f661-4351-af64-b6d1f84cde71 · outbound

This paper cites Dahlman, S.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G Dahlman, S

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:12:56.547081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 58eae7fc-89cc-49be-b55c-ab7676db067c · outbound

This paper cites Millimeter Wave Mobile Communications for 5G Cellular: It Will Work!.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G Millimeter Wave Mobile Communications for 5G Cellular: It Will Work!

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:12:56.533327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e24a1043-7070-4f89-96f9-76112484c530 · outbound

This paper cites BERTScore: Evaluating Text Generation with BERT.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G BERTScore: Evaluating Text Generation with BERT

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-16T04:12:56.180553Z

Source-reported events for the cited work

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Observation 814aea8f-ac95-4888-a641-57f82b42b38c · outbound

This paper cites Meteor: An Automatic Metric for MT Evaluation with High Levels of Correlation with Human Judgments,.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G Meteor: An Automatic Metric for MT Evaluation with High Levels of Correlation with Human Judgments,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:12:56.517444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5ee38793-6654-4506-996a-a8eaa7009770 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-16T04:12:56.189697Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3f82be8-0002-41d8-836c-d1dac0728e14 · outbound

This paper cites Mobile Traffic Prediction from Raw Data Using LSTM Networks,.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G Mobile Traffic Prediction from Raw Data Using LSTM Networks,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:12:56.501346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8f5ab90f-0672-4116-9cf8-2ccbb66594f8 · outbound

This paper cites Language Models are Unsupervised Multitask Learners,.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G Language Models are Unsupervised Multitask Learners,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:12:56.486603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0a4a5e8e-9d57-416d-9133-70fa4f94f6c3 · outbound

This paper cites an unresolved cited work.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G Unresolved cited work

Reference 42

Resolution: unresolved; raw_fallback, observed 2026-08-16T04:12:56.471365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3da6a77a-ef16-4b6d-bfac-b270e60e184e · outbound

This paper cites an unresolved cited work.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G Unresolved cited work

Reference 43

Resolution: unresolved; raw_fallback, observed 2026-08-16T04:12:56.457451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 89eb9be9-83d9-468e-b60d-e521e7ab14e6 · outbound

This paper cites Increase throughput by 10%,.

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G Increase throughput by 10%,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:12:56.443123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Pith citing papers

No inbound Pith citation observations are available.