5 citations · 11 across the 11 of their papers we have counts for
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cs.AI2026
The Devil is in the Spectrum: Mitigating Representation Collapse in LLMs via Topologically Regularized Side-Path
Yiheng Tao, Kaiwen Cheng, Yao Lu +2
Large Language Models (LLMs) are fundamentally limited by representation collapse, a bottleneck that severely degrades long-context performance. We identify that existing approache…
cs.CV2026
JetViT: Efficient High-Resolution Vision Transformer with Post-Training Attention Search
Dongyun Zou, Zhuoyang Zhang, Junyu Chen +8
We introduce JetViT, a novel family of hybrid-architecture Vision Transformer (ViT) models that match the accuracy of state-of-the-art full-attention vision foundation models while…
cs.RO2026
ForeAct: Steering Your VLA with Efficient Visual Foresight Planning
Zhuoyang Zhang, Shang Yang, Qinghao Hu +5
Vision-Language-Action (VLA) models convert high-level language instructions into concrete, executable actions, a task that is especially challenging in open-world environments. We…