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Ruoxue Li

2 accepted papers

2026

Cog-RAG: Cognitive-Inspired Dual-Hypergraph with Theme Alignment Retrieval-Augmented Generation

AAAI 2026technical

Retrieval-Augmented Generation (RAG) enhances the response quality and domain-specific performance of large language models (LLMs) by incorporating external knowledge to combat hallucinations. In recent research, graph structures have been integrated into RAG to enhance the capture of semantic relat

Cited by 0SourcePDFScholar
2024

A Novel Cross-Sensor Self-Supervised Learning Method for Rotating Machinery Fault Diagnosis

ICASSP 2024accepted

Fault diagnosis is crucial in mechanical prognostics and health management. However, fault features extracted from single-sensor data are limited in complex operating environments. Extracting complementary and robust fault features from multi-sensor monitoring data is essential, especially under lim…

Cited by 0SourceScholar