7 papers
NPG-Muse: Scaling Long Chain-of-Thought Reasoning with NP-Hard Graph Problems
Yuyao Wang, Bowen Liu, Jianheng Tang +6
Reasoning Large Language Models (RLLMs) have recently achieved remarkable progress on complex reasoning tasks, largely enabled by their long chain-of-thought (Long CoT) capabilitie…
How does Misinformation Affect Large Language Model Behaviors and Preferences?
Miao Peng, Nuo Chen, Jianheng Tang +1
Large Language Models (LLMs) have shown remarkable capabilities in knowledge-intensive tasks, while they remain vulnerable when encountering misinformation. Existing studies have e…
UniGAD: Unifying Multi-level Graph Anomaly Detection
Yiqing Lin, Jianheng Tang, Chenyi Zi +3
Graph Anomaly Detection (GAD) aims to identify uncommon, deviated, or suspicious objects within graph-structured data. Existing methods generally focus on a single graph object typ…
GCoder: Improving Large Language Model for Generalized Graph Problem Solving
Qifan Zhang, Xiaobin Hong, Jianheng Tang +5
Large Language Models (LLMs) have demonstrated strong reasoning abilities, making them suitable for complex tasks such as graph computation. Traditional reasoning steps paradigm fo…
Graph Pre-Training Models Are Strong Anomaly Detectors
Jiashun Cheng, Zinan Zheng, Yang Liu +5
Graph Anomaly Detection (GAD) is a challenging and practical research topic where Graph Neural Networks (GNNs) have recently shown promising results. The effectiveness of existing…
GraphArena: Evaluating and Exploring Large Language Models on Graph Computation
Jianheng Tang, Qifan Zhang, Yuhan Li +2
The ``arms race'' of Large Language Models (LLMs) demands new benchmarks to examine their progresses. In this paper, we introduce GraphArena, a benchmarking tool designed to evalua…