Author

Jun-Yi Wu

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Preprint Sep 2026

CAST: Reconstruction-Coupled Acceleration of Interactive World Models

Interactive world models must respond quickly to controls while preserving scene consistency. Existing acceleration methods can miss heterogeneous control responses and spatial transport when recovering skipped features. We observe that interaction-induced feature changes correlate with approximation error, while low-f...

Le-Yang Chen, Jun-Yi Wu, Fan-Qing Kong et al. · 0 citations

Preprint Oct 2026

VASC: Value-Aware Sparse Attention with Cross-Layer Memory for Efficient 3D Reconstruction

Feed-forward 3D vision models such as VGGT have achieved remarkable progress, unifying camera estimation and dense scene reconstruction in a single pass. However, their quadratic global attention makes long image sequences expensive, while existing sparse methods may favor highly attended yet value-redundant regions. T...

Jun-Yi Wu, Fan-Qing Kong, Le-Yang Chen et al. · 0 citations

#artificial intelligence Preprint Sep 2026

JustQuant: You Don't Need Smoothing, SVD, or Rotation for 4-Bit Activation Quantization

JustQuant is proposed, a simple yet effective framework that moves the complexity of low-bit quantization from deployment-time operators into the training process and introduces Theseus QAD, a quantization-aware distillation method that progressively applies multi-level supervision, analogous to the gradual replacement...

Kai-Cheng Yang, Kai-Sen Yang, Chun-Yu Liu et al. · 0 citations

Jul 2026

Factorized Spectral Representations for Reinforcement Learning

FaStR is proposed, which fits this decomposition with a noise contrastive objective, producing separate state, action, and next-state encoders that together form a single spectral representation.

Junyi Wu, Dan Li · arXiv.org · 0 citations