4 papers
PrivGemo: Privacy-Preserving Dual-Tower Graph Retrieval for Empowering LLM Reasoning with Memory Augmentation
Xingyu Tan, Xiaoyang Wang, Qing Liu +4
Knowledge graphs (KGs) provide structured evidence that can ground large language model (LLM) reasoning for knowledge-intensive question answering. However, many practical KGs are…
MMAPG: A Training-Free Framework for Multimodal Multi-hop Question Answering via Adaptive Planning Graphs
Yiheng Hu, Xiaoyang Wang, Qing Liu +4
Multimodal Multi-hop question answering requires integrating information from diverse sources, such as images and texts, to derive answers. Existing methods typically rely on seque…
HydraRAG: Structured Cross-Source Enhanced Large Language Model Reasoning
Xingyu Tan, Xiaoyang Wang, Qing Liu +4
Retrieval-augmented generation (RAG) enhances large language models (LLMs) by incorporating external knowledge. Current hybrid RAG system retrieves evidence from both knowledge gra…
SGPT: Few-Shot Prompt Tuning for Signed Graphs
Zian Zhai, Sima Qing, Xiaoyang Wang +1
Signed Graph Neural Networks (SGNNs) are effective in learning expressive representations for signed graphs but typically require substantial task-specific labels, limiting their a…