16 citations · 32 across the 8 of their papers we have counts for
8 papers
Revisiting the Graph Reasoning Ability of Large Language Models: Case Studies in Translation, Connectivity and Shortest Path
Xinnan Dai, Qihao Wen, Yifei Shen +4
Large Language Models (LLMs) have achieved great success in various reasoning tasks. In this work, we focus on the graph reasoning ability of LLMs. Although theoretical studies pro…
Learning on Graphs with Large Language Models(LLMs): A Deep Dive into Model Robustness
Kai Guo, Zewen Liu, Zhikai Chen +4
Large Language Models (LLMs) have demonstrated remarkable performance across various natural language processing tasks. Recently, several LLMs-based pipelines have been developed t…
IterAlign: Iterative Constitutional Alignment of Large Language Models
Xiusi Chen, Hongzhi Wen, Sreyashi Nag +5
With the rapid development of large language models (LLMs), aligning LLMs with human values and societal norms to ensure their reliability and safety has become crucial. Reinforcem…
Content Knowledge Identification with Multi-Agent Large Language Models (LLMs)
Kaiqi Yang, Yucheng Chu, Taylor Darwin +6
Teachers' mathematical content knowledge (CK) is of vital importance and need in teacher professional development (PD) programs. Computer-aided asynchronous PD systems are the most…
Are Large Language Models (LLMs) Good Social Predictors?
Kaiqi Yang, Hang Li, Hongzhi Wen +3
The prediction has served as a crucial scientific method in modern social studies. With the recent advancement of Large Language Models (LLMs), efforts have been made to leverage L…
Investigating Out-of-Distribution Generalization of GNNs: An Architecture Perspective
Kai Guo, Hongzhi Wen, Wei Jin +3
Graph neural networks (GNNs) have exhibited remarkable performance under the assumption that test data comes from the same distribution of training data. However, in real-world sce…
Copyright Protection in Generative AI: A Technical Perspective
Jie Ren, Han Xu, Pengfei He +10
Generative AI has witnessed rapid advancement in recent years, expanding their capabilities to create synthesized content such as text, images, audio, and code. The high fidelity a…
Label-free Node Classification on Graphs with Large Language Models (LLMS)
Zhikai Chen, Haitao Mao, Hongzhi Wen +5
In recent years, there have been remarkable advancements in node classification achieved by Graph Neural Networks (GNNs). However, they necessitate abundant high-quality labels to…