3 papers
cs.LG2026
SAIR: Cost-Efficient Multi-Stage ML Pipeline Autoscaling via In-Context Reinforcement Learning
Jianchang Su, Yifan Zhang, Shengkai Lin +4
Multi-stage ML inference pipelines are difficult to autoscale due to heterogeneous resources, cross-stage coupling, and dynamic bottleneck migration. We present SAIR, an autoscalin…
cs.OS2025
gpu_ext: Extensible OS Policies for GPUs via eBPF
Yusheng Zheng, Tong Yu, Yiwei Yang +8
Performance in modern GPU-centric systems increasingly depends on resource management policies, including memory placement, scheduling, and observability. However, uniform policies…
cs.MA2025
PromptSculptor: Multi-Agent Based Text-to-Image Prompt Optimization
Dawei Xiang, Wenyan Xu, Kexin Chu +5
The rapid advancement of generative AI has democratized access to powerful tools such as Text-to-Image models. However, to generate high-quality images, users must still craft deta…