Statistical Estimation of Adversarial Risk in Large Language Models under Best-of-N Sampling

Statistical Estimation of Adversarial Risk in Large Language Models under Best-of-N Sampling explores A scalable methodology for assessing real-world risk in LLMs under adversarial conditions, with code availability promising research integration.. Commercial viability score: 5/10 in AI Safety.