Shinichi Nakagawa

A Japanese-Dietitian Prompt Systematically Shifts Portion Estimates in LLM-Based Nutrient Estimation from Food Images: A Multi-Dataset, Multi-Model Study

Background/Objectives: In food-image nutrient estimation with vision-language models (VLMs), portion size is a dominant source of error, yet how a prompt shifts the estimated amount—and in which direction—remains uncharacterized. We tested whether a Japanese-dietitian prompt acts as a systematic, directional influence...