collaborators

16 papers

cs.CV2026

SVG-EAR: Parameter-Free Linear Compensation for Sparse Video Generation via Error-aware Routing

Xuanyi Zhou, Qiuyang Mang, Shuo Yang +7

Diffusion Transformers (DiTs) have become a leading backbone for video generation, yet their quadratic attention cost remains a major bottleneck. Sparse attention reduces this cost…

cs.DC2026

Prism: Cost-Efficient Multi-LLM Serving via GPU Memory Ballooning

Shan Yu, Yifan Qiao, Mingyuan Ma +18

Inference providers must maintain availability for many LLMs, including low-volume but essential models, making resource efficiency increasingly important as token prices fall. Ana…

cs.LG2026

BlendServe: Optimizing Offline Inference for Auto-regressive Large Models with Resource-aware Batching

Yilong Zhao, Shuo Yang, Kan Zhu +5

Offline batch inference, which leverages the flexibility of request batching to achieve higher throughput and lower costs, is becoming more popular for latency-insensitive applicat…

cs.LG2026

vAttention: Verified Sparse Attention

Aditya Desai, Kumar Krishna Agrawal, Shuo Yang +5

State-of-the-art sparse attention methods for reducing decoding latency fall into two main categories: approximate top- (and its extension, top-) and recently introduced samp…

cs.AR2026

NasZip: Software and Hardware Co-Design to Accelerate Approximate Nearest Neighbor Search with DIMM-Based Near-Data Processing

Cheng Zou, Shuo Yang, Chen Nie +6

As large language models (LLMs) continue to advance, retrieval-augmented generation (RAG) has become the key mechanism for expanding model knowledge and reducing hallucinations. Ce…

cs.CV2026

Sparse VideoGen2: Accelerate Video Generation with Sparse Attention via Semantic-Aware Permutation

Shuo Yang, Haocheng Xi, Yilong Zhao +10

Diffusion Transformers (DiTs) are essential for video generation but suffer from significant latency due to the quadratic complexity of attention. By computing only critical tokens…