Author

Shengze Cai

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Preprint Sep 2026

Trajectory-Level Mode Guidance for Controllable Diffusion-Based Multi-Robot Motion Planning

Motion planning often admits multiple feasible solutions, making multimodal generation valuable, particularly for flexible multi-robot coordination. Diffusion models naturally learn such trajectory distributions, yet incorporating coarse and partial trajectory priors without restricting generation remains challenging....

Tian-You Yu, Sheng-Ze Cai, Chao Xu · 0 citations

#machine learning Preprint Sep 2026

Learning Provable Neural Network Observer for Uncertain Dynamical Systems

In many safety-critical applications, control of uncertain dynamical systems relies on observers that estimate states and external disturbances. Neural network observers can improve estimation accuracy, but certifying their Lyapunov stability via Linear Matrix Inequality (LMI) constraints leads to large-scale semidefin...

Zhang-Yi Wang, Jia-Xu Liu, Chen Song et al. · 0 citations

Open access Aug 2026

An efficient graph-transformer operator for learning physical dynamics with manifolds embedding

An efficient graph-transformer operator, named PhysGTO, is shown for learning physical dynamics through explicit manifold embeddings in both physical and latent spaces, showing strong flexibility, scalability, and generalization across diverse physical systems.

Peng-Wei Liu, Xingyu Ren, Peng-Kai Wang et al. · Communications AI & Computin... · 0 citations

Preprint Aug 2026

DART: Decoded Attention over Recurrent States for Efficient Long-Context Sequence Modeling

DART (Decoded Attention over Recurrent sTates), which retains the chunk state contributions produced by the Mamba-2 chunked scan as chunk state memories, decodes token-conditioned keys and values from these memories, and performs state-memory attention (SMA) over the resulting KV pairs.

Yixiao Qian, Song Chen, Pengkai Wang et al. · 0 citations