8 papers
Prompt Perturbation for Reliable LLM Evaluation over Comparison Graphs
Dong Huang, Jianbo Sun, Pengkun Yang
Evaluating large language models (LLMs) is important for understanding their capabilities, comparing competing systems, and supporting the deployment of reliable models in practice…
Attributed Network Alignment: Statistical Limits and Efficient Algorithm
Dong Huang, Chenyang Tian, Pengkun Yang
This paper studies the problem of recovering a hidden vertex correspondence between two correlated graphs when both edge weights and node features are observed. While most existing…
Testing Correlation in Graphs by Counting Bounded Degree Motifs
Dong Huang, Pengkun Yang
We investigate the problem of detecting correlation between two ErdÅs-Rényi graphs , formulated as a hypothesis testing problem: under the null hypothesis, the two graphs…
Fundamental Limits of Community Detection in Contextual Multi-Layer Stochastic Block Models
Shuyang Gong, Dong Huang, Zhangsong Li
We consider the problem of community detection from the joint observation of a high-dimensional covariate matrix and sparse networks, all encoding noisy, partial information ab…
Information-Theoretic and Computational Limits of Correlation Detection under Graph Sampling
Dong Huang, Pengkun Yang
Correlation analysis is a fundamental problem in statistics. In this paper, we consider the correlation detection problem between a pair of Erdos-Renyi graphs. Specifically, the pr…
Variational Estimators for Node Popularity Models
Jony Karki, Dongzhou Huang, Yunpeng Zhao
Node popularity is recognized as a key factor in modeling real-world networks, capturing heterogeneity in connectivity across communities. This concept is equally important in bipa…