12 citations · 29 across the 16 of their papers we have counts for
9 papers · 1 filter
Transferable Unsupervised Outlier Detection Framework for Human Semantic Trajectories
Zheng Zhang, Hossein Amiri, Dazhou Yu +3
Semantic trajectories, which enrich spatial-temporal data with textual information such as trip purposes or location activities, are key for identifying outlier behaviors critical…
Taxonomy Tree Generation from Citation Graph
Yuntong Hu, Zhuofeng Li, Zheng Zhang +4
Constructing taxonomies from citation graphs is essential for organizing scientific knowledge, facilitating literature reviews, and identifying emerging research trends. However, m…
Representation Learning of Geometric Trees
Zheng Zhang, Allen Zhang, Ruth Nelson +2
Geometric trees are characterized by their tree-structured layout and spatially constrained nodes and edges, which significantly impacts their topological attributes. This inherent…
TEG-DB: A Comprehensive Dataset and Benchmark of Textual-Edge Graphs
Zhuofeng Li, Zixing Gou, Xiangnan Zhang +6
Text-Attributed Graphs (TAGs) augment graph structures with natural language descriptions, facilitating detailed depictions of data and their interconnections across various real-w…
TAGA: Text-Attributed Graph Self-Supervised Learning by Synergizing Graph and Text Mutual Transformations
Zheng Zhang, Yuntong Hu, Bo Pan +2
Text-Attributed Graphs (TAGs) enhance graph structures with natural language descriptions, enabling detailed representation of data and their relationships across a broad spectrum…
Link Prediction on Textual Edge Graphs
Chen Ling, Zhuofeng Li, Yuntong Hu +5
Textual-edge Graphs (TEGs), characterized by rich text annotations on edges, are increasingly significant in network science due to their ability to capture rich contextual informa…
GRAG: Graph Retrieval-Augmented Generation
Yuntong Hu, Zhihan Lei, Zheng Zhang +3
Naive Retrieval-Augmented Generation (RAG) focuses on individual documents during retrieval and, as a result, falls short in handling networked documents which are very popular in…
Position-Aware Parameter Efficient Fine-Tuning Approach for Reducing Positional Bias in LLMs
Zheng Zhang, Fan Yang, Ziyan Jiang +5
Recent advances in large language models (LLMs) have enhanced their ability to process long input contexts. This development is particularly crucial for tasks that involve retrievi…
Distilling Large Language Models for Text-Attributed Graph Learning
Bo Pan, Zheng Zhang, Yifei Zhang +2
Text-Attributed Graphs (TAGs) are graphs of connected textual documents. Graph models can efficiently learn TAGs, but their training heavily relies on human-annotated labels, which…