Paper Citation Record · LEDGER

Reasoning Language Models for Root Cause Analysis in 5G Wireless Networks

As of 15 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 4 inbound Pith citation observations for arXiv:2507.21974.

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

pith.paper-citation-record.v1
2507.21974 v1

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T12:14:47.048297Z

measured 20 of 20 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T00:17:28.926641Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T09:03:15.685485Z

Reference resolution

16 of 16 outbound references displayed

verified exact1
verified fuzzy9
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d496687f-9e07-48f0-a13e-4c1bd1412660 · outbound

This paper cites ICASSP-SPGC 2022: Root cause analysis for wireless network fault localization,.

Reasoning Language Models for Root Cause Analysis in 5G Wireless Networks ICASSP-SPGC 2022: Root cause analysis for wireless network fault localization,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:14:48.954604Z

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 f34c8987-1f3d-46f7-a06c-fa2ebb07dbd8 · outbound

This paper cites Machine learning based root cause analysis for sdn network,.

Reasoning Language Models for Root Cause Analysis in 5G Wireless Networks Machine learning based root cause analysis for sdn network,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:14:48.839595Z

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 1338c9e6-0a0f-4b63-9077-c880ff382894 · outbound

This paper cites Root cause analysis of network failures using machine learning and summarization techniques,.

Reasoning Language Models for Root Cause Analysis in 5G Wireless Networks Root cause analysis of network failures using machine learning and summarization techniques,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:14:48.691674Z

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 1cf30f0e-f0b4-4fdd-919a-fc33adb43a68 · outbound

This paper cites Survey on Models and Techniques for Root-Cause Analysis.

Reasoning Language Models for Root Cause Analysis in 5G Wireless Networks Survey on Models and Techniques for Root-Cause Analysis

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T12:14:46.102532Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fefc7232-c924-4b63-8818-ee2ebdb2f673 · outbound

This paper cites Graph neural network based root cause analysis using multivariate time-series kpis for wireless networks,.

Reasoning Language Models for Root Cause Analysis in 5G Wireless Networks Graph neural network based root cause analysis using multivariate time-series kpis for wireless networks,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:14:48.543384Z

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 854de083-7231-449a-8e9f-aee9d504632c · outbound

This paper cites On the use of spatial graphs for performance degradation root-cause analysis toward self-healing mobile networks,.

Reasoning Language Models for Root Cause Analysis in 5G Wireless Networks On the use of spatial graphs for performance degradation root-cause analysis toward self-healing mobile networks,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:14:48.384809Z

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 548a139e-5dc1-4bee-82fc-6d5d0b859770 · outbound

This paper cites TN-AutoRCA: Benchmark Construction and Agentic Framework for Self-Improving Alarm-Based Root Cause Analysis in Telecommunication Networks.

Reasoning Language Models for Root Cause Analysis in 5G Wireless Networks TN-AutoRCA: Benchmark Construction and Agentic Framework for Self-Improving Alarm-Based Root Cause Analysis in Telecommunication Networks

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-08-06T12:14:47.534580Z

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 e4a00edb-8f6d-40b5-b5a5-207f5d1b2e5e · outbound

This paper cites Exploring llm-based agents for root cause analysis,.

Reasoning Language Models for Root Cause Analysis in 5G Wireless Networks Exploring llm-based agents for root cause analysis,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:14:48.219359Z

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 1861ad7d-a1b9-4716-a492-1440667a4673 · outbound

This paper cites Rcagent: Cloud root cause analysis by autonomous agents with tool-augmented large language models,.

Reasoning Language Models for Root Cause Analysis in 5G Wireless Networks Rcagent: Cloud root cause analysis by autonomous agents with tool-augmented large language models,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:14:48.073810Z

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 1db3cce4-99b8-4a3c-91b4-d048b3b2c804 · outbound

This paper cites Flow-of-Action: SOP Enhanced LLM-Based Multi-Agent System for Root Cause Analysis,.

Reasoning Language Models for Root Cause Analysis in 5G Wireless Networks Flow-of-Action: SOP Enhanced LLM-Based Multi-Agent System for Root Cause Analysis,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:14:47.903623Z

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 440c907f-dc8c-4df5-84a8-3567eecc5d00 · outbound

This paper cites Training language models to follow instructions with human feedback,.

Reasoning Language Models for Root Cause Analysis in 5G Wireless Networks Training language models to follow instructions with human feedback,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:14:47.738973Z

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 5c906187-d154-40eb-87cb-f443a2eb7158 · outbound

This paper cites SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training.

Reasoning Language Models for Root Cause Analysis in 5G Wireless Networks SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T12:14:46.771375Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9cdc0897-7ed5-4149-a32c-53101a39cb66 · outbound

This paper cites Do NOT Think That Much for 2+3=? On the Overthinking of o1-Like LLMs.

Reasoning Language Models for Root Cause Analysis in 5G Wireless Networks Do NOT Think That Much for 2+3=? On the Overthinking of o1-Like LLMs

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T12:14:46.853554Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 12f9fc4b-9763-4d32-8135-0fa297471706 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Reasoning Language Models for Root Cause Analysis in 5G Wireless Networks Proximal Policy Optimization Algorithms

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T12:14:46.929231Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c4388cc-5180-4802-8236-b7de557dc247 · outbound

This paper cites HybridFlow: A Flexible and Efficient RLHF Framework.

Reasoning Language Models for Root Cause Analysis in 5G Wireless Networks HybridFlow: A Flexible and Efficient RLHF Framework

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T12:14:46.985658Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07a593a1-17b3-4522-b61b-9a933d971e33 · outbound

This paper cites Qwen3 Technical Report.

Reasoning Language Models for Root Cause Analysis in 5G Wireless Networks Qwen3 Technical Report

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T12:14:47.048297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 2d23fcab-399b-4e81-adfc-7fb2cf8bdddd · inbound

TeleCom-Bench: How Far Are Large Language Models from Industrial Telecommunication Applications? cites this paper.

TeleCom-Bench: How Far Are Large Language Models from Industrial Telecommunication Applications? Reasoning Language Models for Root Cause Analysis in 5G Wireless Networks

Reference 50

Resolution: verified exact; arxiv_id, observed 2026-05-20T11:28:14.657022Z

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 17f6492f-5404-4f03-9f86-2988ac74c19c · inbound

HPO: Hysteretic Policy Optimization for Stable and Efficient Training under Sparse-Reward Regime cites this paper.

HPO: Hysteretic Policy Optimization for Stable and Efficient Training under Sparse-Reward Regime Reasoning Language Models for Root Cause Analysis in 5G Wireless Networks

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-06-29T09:03:15.687531Z

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 66956e6b-3eef-4eea-a3be-235af4ca28d7 · inbound

PropLLM: Propagation-Aware Scene Reconstruction for Network Fault Diagnosis cites this paper.

PropLLM: Propagation-Aware Scene Reconstruction for Network Fault Diagnosis Reasoning Language Models for Root Cause Analysis in 5G Wireless Networks

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-06-28T19:02:34.355926Z

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 59ea17cf-848d-4afe-bbdb-39e7b5ee72dd · inbound

WirelessOpsAgent: A Benchmark and Agent Design for Action Assurance in Wireless Networks cites this paper.

WirelessOpsAgent: A Benchmark and Agent Design for Action Assurance in Wireless Networks Reasoning Language Models for Root Cause Analysis in 5G Wireless Networks

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-12T00:17:28.926641Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.