Human Evaluation Protocol

Human evaluation protocols are crucial for assessing the performance of increasingly sophisticated AI models, particularly in text-to-image, text-to-video, and natural language generation. Current research emphasizes improving the reliability, reproducibility, and practicality of these protocols by developing standardized guidelines, addressing inherent biases in human judgment, and exploring alternative evaluation methods beyond simple Likert scales. This work aims to create more robust and trustworthy benchmarks for evaluating AI systems, ultimately leading to more accurate and impactful model development across various applications. The development of publicly available datasets and tools is a key trend, fostering collaboration and accelerating progress in the field.