activity
20232026
most citedRethinking Benchmark and Contamination for Language Models with Rephrased Samples

7 citations · 22 across the 18 of their papers we have counts for

collaborators
Showing 2025Show all

9 papers · 1 filter

cs.AI2025★ 1 cited

Barbarians at the Gate: How AI is Upending Systems Research

Audrey Cheng, Shu Liu, Melissa Pan +14

Artificial Intelligence (AI) is starting to transform the research process as we know it by automating the discovery of new solutions. Given a task, the typical AI-driven approach…

cs.LG2025

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.LG2025

SLA: Beyond Sparsity in Diffusion Transformers via Fine-Tunable Sparse-Linear Attention

Jintao Zhang, Haoxu Wang, Kai Jiang +10

In Diffusion Transformer (DiT) models, particularly for video generation, attention latency is a major bottleneck due to the long sequence length and the quadratic complexity. We f…

cs.CV2025

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…

cs.DC2025

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.NI2025★ 1 cited

An Extensible Software Transport Layer for GPU Networking

Yang Zhou, Zhongjie Chen, Ziming Mao +11

Fast-evolving machine learning (ML) workloads have increasing requirements for networking. However, host network transport on RDMA NICs is hard to evolve, causing problems for ML w…

cs.CV2025★ 2 cited

WorldModelBench: Judging Video Generation Models As World Models

Dacheng Li, Yunhao Fang, Yukang Chen +10

Video generation models have rapidly progressed, positioning themselves as video world models capable of supporting decision-making applications like robotics and autonomous drivin…

cs.LG2025

Twilight: Adaptive Attention Sparsity with Hierarchical Top- Pruning

Chaofan Lin, Jiaming Tang, Shuo Yang +6

Leveraging attention sparsity to accelerate long-context large language models (LLMs) has been a hot research topic. However, current algorithms such as sparse attention or key-val…

cs.CV2025★ 1 cited

Sparse VideoGen: Accelerating Video Diffusion Transformers with Spatial-Temporal Sparsity

Haocheng Xi, Shuo Yang, Yilong Zhao +11

Diffusion Transformers (DiTs) dominate video generation but their high computational cost severely limits real-world applicability, usually requiring tens of minutes to generate a…