MT Bench

MT Bench, encompassing a broad range of benchmarks, aims to rigorously evaluate the capabilities of large language and multimodal models across diverse tasks, including visual perception, video quality assessment, and dialogue generation. Current research focuses on developing standardized benchmarks with fine-grained difficulty annotations and realistic validation procedures, often employing large language models themselves for evaluation. These benchmarks are crucial for identifying limitations in current models and guiding the development of more robust and reliable AI systems with improved generalization and safety, impacting various fields from healthcare to scientific research.