TN-AutoRCA: Benchmark Construction and Agentic Framework for Self-Improving Alarm-Based Root Cause Analysis in Telecommunication Networks
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arXiv
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| Autori principali: | , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
| Accesso online: | |
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| _version_ | 1866918105239781376 |
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| author | Wu, Keyu Yu, Qianjin Mei, Manlin Liu, Ruiting Wang, Jun Zhang, Kailai Bao, Yelun |
| author_facet | Wu, Keyu Yu, Qianjin Mei, Manlin Liu, Ruiting Wang, Jun Zhang, Kailai Bao, Yelun |
| contents | Root Cause Analysis (RCA) in telecommunication networks is a critical task, yet it presents a formidable challenge for Artificial Intelligence (AI) due to its complex, graph-based reasoning requirements and the scarcity of realistic benchmarks. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_18190 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | TN-AutoRCA: Benchmark Construction and Agentic Framework for Self-Improving Alarm-Based Root Cause Analysis in Telecommunication Networks Wu, Keyu Yu, Qianjin Mei, Manlin Liu, Ruiting Wang, Jun Zhang, Kailai Bao, Yelun Computation and Language Root Cause Analysis (RCA) in telecommunication networks is a critical task, yet it presents a formidable challenge for Artificial Intelligence (AI) due to its complex, graph-based reasoning requirements and the scarcity of realistic benchmarks. |
| title | TN-AutoRCA: Benchmark Construction and Agentic Framework for Self-Improving Alarm-Based Root Cause Analysis in Telecommunication Networks |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2507.18190 |