1 citations · 3 across the 13 of their papers we have counts for
18 papers
Know the Shape, Find the Fault: Topology-Conditioned Diagnosis of Multi-Agent LLM Failures
Xinwen Liu, Zhuocheng Pan, Isabella Zhu +3
Multi-agent LLM systems coordinate task execution through exchanges of information among agents. When coordination breaks down, similar symptoms in execution traces can reflect dif…
Second-Order Image Characterization with Distortion and Secrecy
Cao Daming
Image characterization relates coding budgets to the probability carried by source cells and their output images. At second order, refining a cell can reveal unavailable informatio…
DeepShare: Assurance-Driven Deep Learning Job Scheduling for Multi-Tenant Clusters
Jinghao Wang, Yihang Zhou, Xiao Zhou +5
Multi-tenant GPU clusters frequently remain underutilized even when tenants experience long queueing delays, because quota control, queue ordering, preemption, and GPU sharing are…
Latency-Aware Orchestration for Multi-Agent LLM Workflows on Heterogeneous GPUs
Jinghao Wang, Yifeng Zhang, Xiao Zhou +7
Concurrent multi-agent workflows expose future dependencies and serving-state requirements while running on heterogeneous GPU pools with time-varying load, model residency, and res…
ElastiCo: Elastic Configuration and Interference-Aware Orchestration for GPU Clusters
Jinghao Wang, Yihang Zhou, Xiaoyang Sun +5
Modern GPU clusters must simultaneously serve deep learning training and offline large language model inference workloads, yet existing schedulers treat these as isolated resource…
SpecBox: Speculative Sandbox Scheduling for Efficient LLM Agent Serving
Yihui Zhang, Tianyu Wo, Jinghao Wang +7
As LLM agents increasingly rely on the Model Context Protocol (MCP) to invoke isolated external sandboxes, disaggregated sandbox deployment introduces a fundamental tension between…
CrossPool: Efficient Multi-LLM Serving for Cold MoE Models through KV-Cache and Weight Disaggregation
Zhuoren Ye, Tianyu Wo, Dinghao Xue +4
Emerging LLM services increasingly host many sparse MoE models, yet most models receive sparse requests and remain cold. This creates a GPU memory problem: model weights are stable…
Maestro: Workload-Aware Cross-Cluster Scheduling for LLM-Based Multi-Agent Systems
Jinghao Wang, Xiao Zhou, Xiaoyang Sun +6
Large Language Model based Multi-Agent Systems (LLM-MAS) have emerged as a powerful paradigm for tackling complex tasks by breaking them into collaborative workflows of specialized…
An Improved Time Series Anomaly Detection by Applying Structural Similarity
Tiejun Wang, Rui Wang, Xudong Mou +4
Effective anomaly detection in time series is pivotal for modern industrial applications and financial systems. Due to the scarcity of anomaly labels and the high cost of manual la…
CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments
Xudong Mou, Rui Wang, Tiejun Wang +11
Time-series anomaly detection is crucial in AIOps for maintaining large-scale service reliability. In production, streams of Key Performance Indicators (KPI) are high-dimensional,…
RoCA: Robust Contrastive One-class Time Series Anomaly Detection with Contaminated Data
Xudong Mou, Rui Wang, Bo Li +4
The accumulation of time-series signals and the absence of labels make time-series Anomaly Detection (AD) a self-supervised task of deep learning. Methods based on normality assump…
Motion Forecasting for Autonomous Vehicles: A Survey
Jianxin Shi, Jinhao Chen, Yuandong Wang +4
In recent years, the field of autonomous driving has attracted increasingly significant public interest. Accurately forecasting the future behavior of various traffic participants…
RobotDiffuse: Diffusion-Based Motion Planning for Redundant Manipulators with the ROP Obstacle Avoidance Dataset
Xudong Mou, Xiaohan Zhang, Tiejun Wang +5
Redundant manipulators, with their higher Degrees of Freedom (DoFs), offer enhanced kinematic performance and versatility, making them suitable for applications like manufacturing,…
LDPRecover: Recovering Frequencies from Poisoning Attacks against Local Differential Privacy
Xinyue Sun, Qingqing Ye, Haibo Hu +4
Local differential privacy (LDP), which enables an untrusted server to collect aggregated statistics from distributed users while protecting the privacy of those users, has been wi…
Deep Contrastive One-Class Time Series Anomaly Detection
Rui Wang, Chongwei Liu, Xudong Mou +5
The accumulation of time-series data and the absence of labels make time-series Anomaly Detection (AD) a self-supervised deep learning task. Single-normality-assumption-based metho…
Passenger Mobility Prediction via Representation Learning for Dynamic Directed and Weighted Graph
Yuandong Wang, Hongzhi Yin, Tong Chen +4
In recent years, ride-hailing services have been increasingly prevalent as they provide huge convenience for passengers. As a fundamental problem, the timely prediction of passenge…
One-Pass Error Bounded Trajectory Simplification
Xuelian Lin, Shuai Ma, Han Zhang +2
Nowadays, various sensors are collecting, storing and transmitting tremendous trajectory data, and it is known that raw trajectory data seriously wastes the storage, network band a…
Capturing Topology in Graph Pattern Matching
Shuai Ma, Yang Cao, Wenfei Fan +2
Graph pattern matching is often defined in terms of subgraph isomorphism, an NP-complete problem. To lower its complexity, various extensions of graph simulation have been consider…