Scalable Variational Bayesian Fine-Tuning of LLMs via Orthogonalized Low-Rank Adapters
arXiv:2604.03388v1 Announce Type: cross
Abstract: When deploying large language models (LLMs) to safety-critical applications, uncertainty quantification (UQ) is of utmost importance to self-assess the reliability of the LLM-based decisions. However, …