34 citations · 37 across the 10 of their papers we have counts for
5 papers · 1 filter
Split Conformal Interval Length under Huber Contamination
Xiao Zhang, Bowen Zhang, Lie He
Existing analyses of interval length in split conformal prediction largely focus on clean data. However, how contamination at the training and calibration stages alters interval le…
SparLeak: Privacy Leakage from Sparse Attention in LLM Inference on Shared GPUs
Fahao Chen, Linkang Du, Jinhao Zhou +2
Sparse attention is widely used to accelerate long-context inference in modern large language models (LLMs), but its input-dependent execution behavior introduces previously unexpl…
Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement
Qianli Liu, Kaibin Guo, Zicong Hong +5
Expert parallelism has become the prevailing paradigm to serve Mixture-of-Experts (MoE) models. Its efficiency depends on the communication and computation latencies of the GPUs, w…
GraphFlow: A Graph-Based Workflow Management for Efficient LLM-Agent Serving
Ao Li, Shangpeng Yang, Fahao Chen +3
Large Language Model (LLM)-based agents demonstrate strong reasoning and execution capabilities on complex tasks when guided by structured instructions, commonly referred to as wor…
FedGraph: Federated Graph Learning with Intelligent Sampling
Fahao Chen, Peng Li, Toshiaki Miyazaki +1
Federated learning has attracted much research attention due to its privacy protection in distributed machine learning. However, existing work of federated learning mainly focuses…