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Preprint Oct 2026

PhysLDM: Latent Diffusion for High-Fidelity Deformable Simulation

Neural simulation of high-fidelity deformable bodies is a foundational challenge in computer graphics and physical AI. Long-horizon prediction for high-resolution 3D volumetric meshes is difficult: autoregressive methods are susceptible to error accumulation, while direct multi-frame prediction at native resolution is...

Yu Zhang, Xu-Dong Xu, Xin-Gang Pan · 0 citations
Preprint Aug 2026

MegaParts: Scaling Part-Aware 3D Object Generation to 300 Parts via Token-Efficient Autoregressive Modeling

MegaParts, a scalable autoregressive 3D generation framework to address this challenge by combining structured sequence modeling with a token-efficient vector-quantized shape tokenizer, achieves higher mesh quality than baseline autoregressive and diffusion models and suggests that LLM native token-efficient autoregres...

Manwen Liao, Xinyu Lian, Jian Mao et al. · 0 citations

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