A two-stage SFT+RL fine-tuning pipeline for reasoning LLMs achieves 95.86% root cause accuracy on a new synthetic 5G troubleshooting benchmark, TeleLogs.
Exploring llm-based agents for root cause analysis,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.AI 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
Reasoning Language Models for Root Cause Analysis in 5G Wireless Networks
A two-stage SFT+RL fine-tuning pipeline for reasoning LLMs achieves 95.86% root cause accuracy on a new synthetic 5G troubleshooting benchmark, TeleLogs.