Efficient AI Computing,
Transforming the Future.

Projects

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Radial Attention: O(nlogn) Sparse Attention with Energy Decay for Long Video Generation

ArXiv 2025
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A O(nlogn) Sparse Attention Mask for Long Video Generation

LServe: Efficient Long-sequence LLM Serving with Unified Sparse Attention

MLSys 2025
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LServe accelerates long-sequence LLM serving with unified sparse attention for both prefilling and decoding, achieving up to 3.3× speedup over state-of-the-art solution without sacrificing accuracy.

QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM Serving

MLSys 2025
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QServe accelerates large-scale LLM serving on GPUs with QoQ (W4A8KV4) quantization, boosting the generation throughputs by up to 3x over the state-of-the-art solution.

SVDQuant: Absorbing Outliers by Low-Rank Components for 4-Bit Diffusion Models

ICLR 2025
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spotlight
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A new W4A4 quantization paradigm for diffusion models.