From the 1 of 6 linked papers with an AI index.
6 papers
NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation
Guo Chen, Ziwen Li, Maolin Zheng +3
The paper proposes NGM-RAG, a framework that combines graph neural networks with text matching to improve retrieval-augmented generation for tasks requiring multi-hop reasoning and…
Inductive Dual-Polarity Modeling via Static-Dynamic Disentanglement for Dynamic Signed Networks
Yikang Hou, Junjie Huang, Yijun Ran +1
Dynamic signed networks (DSNs) are common in online platforms, where time-stamped positive and negative relations evolve over time. A core task in DSNs is dynamic edge prediction,…
LIRAG: A Lightweight Rerank Reasoning Strategy Framework for Retrieval-Augmented Generation
Guo Chen, Junjie Huang, Huaijin Xie +2
Retrieval-Augmented Generation (RAG) effectively enhances Large Language Models (LLMs) by incorporating retrieved external knowledge into the generation process. Reasoning models i…
A generalized motif-based Naïve Bayes model for sign prediction in complex networks
Yijun Ran, Si-Yuan Liu, Junjie Huang +2
Signed networks, encoding both positive and negative interactions, are essential for modeling complex systems in social and financial domains. Sign prediction, which infers the sig…
Learning to Compress Graphs via Dual Agents for Consistent Topological Robustness Evaluation
Qisen Chai, Yansong Wang, Junjie Huang +1
As graph-structured data grow increasingly large, evaluating their robustness under adversarial attacks becomes computationally expensive and difficult to scale. To address this ch…
Deep learning framework for predicting stochastic take-off and die-out of early spreading
Wenchao He, Tao Jia
Large-scale outbreaks of epidemics, misinformation, or other harmful contagions pose significant threats to human society, yet the fundamental question of whether an emerging outbr…