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cs.AI2025
QuantiPhy: A Quantitative Benchmark Evaluating Physical Reasoning Abilities of Vision-Language Models
Li Puyin, Tiange Xiang, Ella Mao +5
Understanding the physical world is essential for generalist AI agents. However, it remains unclear whether state-of-the-art vision perception models (e.g., large VLMs) can reason…
cs.CV2025
Discovering Latent Graphs with GFlowNets for Diverse Conditional Image Generation
Bailey Trang, Parham Saremi, Alan Q. Wang +6
Capturing diversity is crucial in conditional and prompt-based image generation, particularly when conditions contain uncertainty that can lead to multiple plausible outputs. To ge…
cs.CV2025
Repurposing 2D Diffusion Models with Gaussian Atlas for 3D Generation
Tiange Xiang, Kai Li, Chengjiang Long +5
Recent advances in text-to-image diffusion models have been driven by the increasing availability of paired 2D data. However, the development of 3D diffusion models has been hinder…