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cs.AI2024
Towards Trustworthy Knowledge Graph Reasoning: An Uncertainty Aware Perspective
Bo Ni, Yu Wang, Lu Cheng +2
Recently, Knowledge Graphs (KGs) have been successfully coupled with Large Language Models (LLMs) to mitigate their hallucinations and enhance their reasoning capability, such as i…
cs.AI2024★ 1 cited
SaVe-TAG: LLM-based Interpolation for Long-Tailed Text-Attributed Graphs
Leyao Wang, Yu Wang, Bo Ni +4
Real-world graph data often follows long-tailed distributions, making it difficult for Graph Neural Networks (GNNs) to generalize well across both head and tail classes. Recent adv…
cs.IR2024
Augmenting Textual Generation via Topology Aware Retrieval
Yu Wang, Nedim Lipka, Ruiyi Zhang +6
Despite the impressive advancements of Large Language Models (LLMs) in generating text, they are often limited by the knowledge contained in the input and prone to producing inaccu…