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VGenST-Bench is a benchmark that uses generative models to actively synthesize controlled spatio-temporal reasoning scenarios, with a multi-agent pipeline and human quality control, to evaluate multimodal large language models.
Introduces Flat-Pack Bench, a benchmark for evaluating fine-grained spatio-temporal reasoning in large vision-language models using furniture assembly tasks. Experiments show current LVLMs struggle with tracking and spatial interactions.