12 citations · 29 across the 16 of their papers we have counts for
6 papers · 1 filter
Towards Automatic Evolution Tree Generation from Citation Graphs
Zexing Zhao, Yuntong Hu, Liang Zhao
Surveys remain the primary way researchers grasp the lineage of methods within an AI subfield, but they scale poorly against the current rate of publication. Existing taxonomy-indu…
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…
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…
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…
Balancing Specialized and General Skills in LLMs: The Impact of Modern Tuning and Data Strategy
Zheng Zhang, Chen Zheng, Da Tang +5
This paper introduces a multifaceted methodology for fine-tuning and evaluating large language models (LLMs) for specialized monetization tasks. The goal is to balance general lang…