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cs.RO2025
Noise Fusion-based Distillation Learning for Anomaly Detection in Complex Industrial Environments
Jiawen Yu, Jieji Ren, Yang Chang +7
Anomaly detection and localization in automated industrial manufacturing can significantly enhance production efficiency and product quality. Existing methods are capable of detect…
cs.AI2025
Agent RL Scaling Law: Agent RL with Spontaneous Code Execution for Mathematical Problem Solving
Xinji Mai, Haotian Xu, Zhong-Zhi Li +5
Large Language Models (LLMs) often struggle with mathematical reasoning tasks requiring precise, verifiable computation. While Reinforcement Learning (RL) from outcome-based reward…
cs.CV2025
Component-aware Unsupervised Logical Anomaly Generation for Industrial Anomaly Detection
Xuan Tong, Yang Chang, Qing Zhao +9
Anomaly detection is critical in industrial manufacturing for ensuring product quality and improving efficiency in automated processes. The scarcity of anomalous samples limits tra…