Enhancing Confidence Estimation in Telco LLMs via Twin-Pass CoT-Ensembling

ArXi:2604.13271v1 Announce Type: new Large Language Models (LLMs) are increasingly applied to complex telecommunications tasks, including 3GPP specification analysis and O-RAN network troubleshooting. However, a critical limitation remains: LLM-generated confidence scores are often biased and unreliable, frequently exhibiting systematic overconfidence. This lack of trustworthy self-assessment makes it difficult to verify model outputs and safely rely on them in practice.