activity
20242026
most citedKAN-AD: Time Series Anomaly Detection with Kolmogorov-Arnold Networks

3 citations · 3 across the 4 of their papers we have counts for

collaborators

5 papers

cs.AI2026

Cascade Failure Attribution for Multi-Agent Systems

Jiayi Zhang, Zexin Wang, Degang Sun +4

Large language model (LLM)-based agents have shown strong potential in solving complex tasks through multi-step reasoning, yet they remain vulnerable to execution failures. Accurat…

cs.AI2026

LongRCA Bench: Root-Cause Localization in Long-Horizon Agent Trajectories

Yunfei Zhang, Boyu Feng, Changhua Pei +14

In long agent executions, an early error can persist through later actions and checks, while evidence needed to trace its origin is dispersed across the history. Short histories of…

cs.MA2026

Agent System Operations: Categorization, Challenges, and Future Directions

Zexin Wang, Changhua Pei, Yuanhao Liu +10

As the reasoning capabilities of Large Language Models (LLMs) continue to advance, LLM-based agent systems offer advantages in flexibility and interpretability over traditional sys…

cs.AI2025

A Survey on AgentOps: Categorization, Challenges, and Future Directions

Zexin Wang, Jingjing Li, Quan Zhou +7

As the reasoning capabilities of Large Language Models (LLMs) continue to advance, LLM-based agent systems offer advantages in flexibility and interpretability over traditional sys…

cs.LG2024★ 3 cited

KAN-AD: Time Series Anomaly Detection with Kolmogorov-Arnold Networks

Quan Zhou, Changhua Pei, Fei Sun +6

Time series anomaly detection (TSAD) underpins real-time monitoring in cloud services and web systems, allowing rapid identification of anomalies to prevent costly failures. Most T…