4 papers
Leveraging Multi-Agent System (MAS) and Fine-Tuned Small Language Models (SLMs) for Automated Telecom Network Troubleshooting
Chenhua Shi, Bhavika Jalli, Gregor Macdonald +4
Telecom networks are rapidly growing in scale and complexity, making effective management, operation, and optimization increasingly challenging. Although Artificial Intelligence (A…
Edge-Deployable LLM Fine-Tuning on a Single GPU for Telecom Network Troubleshooting
Chenhua Shi, Bhavika Jalli, John Zou +4
Telecom troubleshooting at edge sites requires low-latency model responses and localized model adaptation to satisfy operational and data sovereignty requirements. However, deployi…
Think Less, Label Better: Multi-Stage Domain-Grounded Synthetic Data Generation for Fine-Tuning Large Language Models in Telecommunications
Chenhua Shi, Gregor Macdonald, Bhavika Jalli +4
The success of large language models (LLMs) depends heavily on large-scale, high-quality instruction-following and reinforcement datasets. However, generating such data through hum…
Causal Intervention Sequence Analysis for Fault Tracking in Radio Access Networks
Chenhua Shi, Joji Philip, Subhadip Bandyopadhyay +1
To keep modern Radio Access Networks (RAN) running smoothly, operators need to spot the real-world triggers behind Service-Level Agreement (SLA) breaches well before customers feel…