Due to the complexity of hotel operation processes, abnormal situations are inevitable, making proactive anomaly prediction essential for ensuring operational stability. Although current deep learning ...

According to @DeepLearningAI, Christoph Meyer and Lars Heling from SAP identified key reasons why AI agents often fail within complex enterprise systems. They explained that agents struggle primarily ...

Abstract: In intelligent manufacturing, the process knowledge graph serves as a vital tool for managing and reasoning about complex process knowledge. Despite its effectiveness, traditional reasoning ...

Large Language Models (LLMs) have set new benchmarks in natural language processing, but their tendency for hallucination—generating inaccurate outputs—remains a critical issue for knowledge-intensive ...

Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to ...

GraphPRM is the first Process Reward Model tailored for graph reasoning tasks, which further enhancing LLMs' mathematical reasoning capabilities on other reasoning domains, including mathematical ...

School of Chemical Engineering, University of Chinese Academy of Sciences, Beijing 100049, China Key Laboratory of Green Process and Engineering, Institute of Process Engineering, Chinese Academy of ...

Graph condensation reduces graph sizes while maintaining performance, addressing the scalability challenges of GNNs caused by computational inefficiencies on large datasets. Existing methods often ...

At a time when every enterprise looks to leverage generative artificial intelligence, data sites are turning their attention to graph databases and knowledge graphs. The global graph database market ...