4 papers
PAGE-RAG: Provenance-Aware Graph Evidence Promotion for Fixed-Budget Multi-hop Retrieval-Augmented Generation
Haokun Deng, Xunkai Li, Hongchao Qin +1
Multi-hop question answering in retrieval-augmented gener?ation (RAG) often benefits from retrieving beyond the few candidates that will finally be read: narrow retrieval can miss…
OpenMAG: A Comprehensive Benchmark for Multimodal-Attributed Graph
Chenxi Wan, Xunkai Li, Yilong Zuo +6
Multimodal-Attributed Graph (MAG) learning has achieved remarkable success in modeling complex real-world systems by integrating graph topology with rich attributes from multiple m…
SPGCL: Simple yet Powerful Graph Contrastive Learning via SVD-Guided Structural Perturbation
Hao Deng, Zhang Guo, Shuiping Gou +1
Graph Neural Networks (GNNs) are sensitive to structural noise from adversarial attacks or imperfections. Existing graph contrastive learning (GCL) methods typically rely on either…
GADPN: Graph Adaptive Denoising and Perturbation Networks via Singular Value Decomposition
Hao Deng, Bo Liu
While Graph Neural Networks (GNNs) excel on graph-structured data, their performance is fundamentally limited by the quality of the observed graph, which often contains noise, miss…