Efficient AI Computing,
Transforming the Future.

Projects

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VILA-U: a Unified Foundation Model Integrating Visual Understanding and Generation

ICLR 2025
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VILA-U is a Unified foundation model that integrates Video, Image, Language understanding and generation.

HART: Efficient Visual Generation with Hybrid Autoregressive Transformer

ICLR 2025
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HART is an autoregressive transformer that generates high resolution images with comparable quality to diffusion models, while offering 4.5-7.7x higher throughput.

LEGO: Spatial Accelerator Generation and Optimization for Tensor Applications

HPCA 2025
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LEGO is an automatic RTL generator for AI accelerators.

Sparse Refinement for Efficient High-Resolution Semantic Segmentation

ECCV 2024
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SparseRefine is a novel approach that enhances dense low-resolution predictions with sparse high-resolution refinements. It achieves significant speedup: 1.5 to 3.7 times when applied to HRNet-W48, SegFormer-B5, Mask2Former-T/L and SegNeXt-L on Cityscapes, with negligible to no loss of accuracy.