4 papers
DABL: Detecting Semantic Anomalies in Business Processes Using Large Language Models
Wei Guan, Jian Cao, Jianqi Gao +2
Detecting anomalies in business processes is crucial for ensuring operational success. While many existing methods rely on statistical frequency to detect anomalies, it's important…
GLOW: Graph-Language Co-Reasoning for Agentic Workflow Performance Prediction
Wei Guan, Jian Cao, Jinyu Cai +3
Agentic Workflows (AWs) have emerged as a promising paradigm for solving complex tasks. However, the scalability of automating their generation is severely constrained by the high…
EMIT: Enhancing MLLMs for Industrial Anomaly Detection via Difficulty-Aware GRPO
Wei Guan, Jun Lan, Jian Cao +3
Industrial anomaly detection (IAD) plays a crucial role in maintaining the safety and reliability of manufacturing systems. While multimodal large language models (MLLMs) show stro…
LogLLM: Log-based Anomaly Detection Using Large Language Models
Wei Guan, Jian Cao, Shiyou Qian +2
Software systems often record important runtime information in logs to help with troubleshooting. Log-based anomaly detection has become a key research area that aims to identify s…