Evaluating and Improving the Robustness of Large Language Models to Input Sequence Variations

Large language models LLMs in production systems face prompt injections, trojans backdoors, and manipulation of automatic quality metrics. This thesis develops models, methods, and algorithms for evaluating and improving LLM robustness to adversarial input sequence variations. We propose Rstabf, ...