1 citations · 1 across the 6 of their papers we have counts for
7 papers
WorldAttention: An Efficient Attention Architecture for Interactive Video World Models
Zeyu Zhang, Jinyuan Mao, Dakai An +6
Leveraging the paradigm of autoregressive diffusion, text-conditioned interactive video world models aim to simulate temporally coherent environments guided by textual instructions…
From LLM Inference to Agentic Workloads: Characterization and Implications for Serving Systems
Chaokun Chang, Yukun Zhou, Kaihua Fu +10
Agentic applications are shifting AI serving from isolated model inference to long-running workloads in which LLMs coordinate tools, environments, and persistent state. However, th…
Rollplex: Cross-Phase GPU Spatial Sharing for Vision Language Model Post-Training
Hanfeng Lu, Tianyu Feng, Suyi Li +8
Vision-language models (VLMs) enable embodied agents to reason and act from visual observations and language instructions. Reinforcement learning (RL) post-training enhances these…
Inferix: A Block-Diffusion based Next-Generation Inference Engine for World Simulation
Inferix Team, Tianyu Feng, Yizeng Han +13
World models serve as core simulators for fields such as agentic AI, embodied AI, and gaming, capable of generating long, physically realistic, and interactive high-quality videos.…
Adaptra: Straggler-Resilient Hybrid-Parallel Training with Pipeline Adaptation
Tianyuan Wu, Lunxi Cao, Hanfeng Lu +8
Training large Deep Neural Network (DNN) models at scale often encounters straggler issues, mostly in communications due to network congestion, RNIC/switch defects, or topological…
SwiftDiffusion: Efficient Diffusion Model Serving with Add-on Modules
Suyi Li, Lingyun Yang, Xiaoxiao Jiang +12
Text-to-image (T2I) generation using diffusion models has become a blockbuster service in today's AI cloud. A production T2I service typically involves a serving workflow where a b…
CaraServe: CPU-Assisted and Rank-Aware LoRA Serving for Generative LLM Inference
Suyi Li, Hanfeng Lu, Tianyuan Wu +6
Pre-trained large language models (LLMs) often need specialization for domain-specific tasks. Low-Rank Adaptation (LoRA) is a popular approach that adapts a base model to multiple…