Chain of Time: In-Context Physical Simulation with Image Generation Models

The introduction of the 'Chain of Time' method marks a significant advancement in the field of vision-language models. This innovative approach enhances physical simulations by generating a series of intermediate images, drawing inspiration from human cognitive processes. Notably, it operates at inference time without the need for additional fine-tuning, making it accessible for various applications. This development not only improves the interpretability of simulations but also opens new avenues for research in machine learning, highlighting the intersection of technology and cognitive science.