MVBench is a dataset for video language models that covers a wide range of temporal tasks, emphasizing temporally-sensitive videos. It facilitates systematic generation of video tasks requiring various temporal abilities, from perception to cognition. MVBench efficiently creates multiple-choice QA for task evaluation by automatically transforming public video annotations, ensuring fairness through ground-truth video annotations and avoiding biased LLM scoring.
No results indexed yet — be the first to submit a score.
Submit a checkpoint and a reproduction script. We will run it, publish the score, and — if it takes the top — annotate the step on the progress chart with your name.