Author

Shiqi Huang

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Preprint Sep 2026

Persistence Forcing: Exploiting Feature Specialization in Pixel-Space Diffusion

Pixel-space diffusion Transformers (DiTs) directly operate on high-dimensional visual data, yet their hidden representations typically undergo uniform refinement across depth. Natural images, however, are inherently organized at different levels of granularity. Global structure can often be represented compactly, where...

Chong Wang, Zi-Xuan Fu, Shi-Qi Huang et al. · 0 citations

#artificial intelligence Preprint Sep 2026

Copy the Same, Distill the Difference: Initializing Linear Vision Transformers

Linear Vision Transformers (ViTs) are designed to replace the attention in Softmax ViTs with the linear-complexity attention operator for more efficient token routing, but they require from-scratch pre-training and typically underperform the original Softmax version. How to initialize linear ViTs both efficiently and e...

Huai-Yuan Qin, Mu-Li Yang, Gabriel James Goenawan et al. · 0 citations

#small language model Preprint Aug 2026

Video-OPSD: Exploiting Privileged Visual Evidence for On-Policy Self-Distillation in Video Large Language Models

Experiments across video understanding and reasoning benchmarks show that the Evidence-Grounded Self-Teacher framework consistently improves upon Standard OPSD across multiple backbones and achieves performance comparable to GRPO while requiring substantially less training time, establishing an effective and efficient...

Zi-Yue Wang, Shiqi Huang, Wei-Wen Xu et al. · 0 citations