Abstract: In the field of graph self-supervised learning (GSSL), graph autoencoders and graph contrastive learning are two mainstream methods. Graph autoencoders aim to learn representations by ...
Summary: Aider currently shows only method signatures in repository maps but lacks call stack tracing and method-level dependency analysis, limiting its effectiveness for understanding code ...
Abstract: As a well-known graph embedding method, Graph Convolutional Networks (GCNs) have been widely applied to recommendation systems and social media analysis, in which privacy concerns regarding ...
School of Automation Engineering, Northeast Electric Power University, Jilin 132012, China Advanced Sensor Research Institution, Northeast Electric Power University, Jilin 132012, China School of ...
While the outputs of large language models (LLMs) appear coherent and useful, the underlying mechanisms guiding these behaviors remain largely unknown. As these models are increasingly deployed in ...
1 School of Computer Science and Technology, Harbin University of Science and Technology, Harbin, China 2 School of Information Engineering, East University of Heilongjiang, Harbin, China Recognizing ...
1 COSCO Shipping Technology Co., Ltd., Shanghai, China. 2 COSCO Shipping Specialized Carriers Co., Ltd., Guangzhou, China. The cost and strict input format requirements of GraphRAG make it less ...
National engineering Research Center of Oil and Gas Pipeline Transportation Safety/MOE Key Laboratory of Petroleum Engineering/Beijing Key Laboratory of Urban Oil and Gas Distribution Technology, ...
No-code Graph RAG employs autonomous agents to integrate enterprise data and domain knowledge with LLMs for context-rich, explainable conversations Graphwise, a leading Graph AI provider, announced ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback