Edmond S. L. Ho

Standard surprisal is typically computed from the linear text prefix, but human reading is non-linear and memory constrained: readers skip words, regress, and do not retain prior context perfectly. We propose a formulation of surprisal conditioned on a reader-specific accessible information state...

Multimodal large language models (MLLMs) have recently achieved remarkable progress in radiology by integrating visual perception with natural language understanding. However, they often generate clinically unsupported descriptions, known as medical hallucinations, which pose serious risks in med...