Zheyuan Zhang

The Effects of In-domain Corpus Size on pre-training BERT

2022 · arXiv (Cornell University)

Many prior language modeling efforts have shown that pre-training on an in-domain corpus can significantly improve performance on downstream domain-specific NLP tasks. However, the difficulties associated with collecting enough in-domain data might discourage researchers from …

Exploring the Cognitive Knowledge Structure of Large Language Models: An Educational Diagnostic Assessment Approach

2023 · arXiv (Cornell University)

Large Language Models (LLMs) have not only exhibited exceptional performance across various tasks, but also demonstrated sparks of intelligence. Recent studies have focused on assessing their capabilities on human exams and revealed their impressive competence …

Can LLMs Convert Graphs to Text-Attributed Graphs?

2024 · arXiv (Cornell University)

Graphs are ubiquitous structures found in numerous real-world applications, such as drug discovery, recommender systems, and social network analysis. To model graph-structured data, graph neural networks (GNNs) have become a popular tool. However, existing GNN …

LLM-Empowered Class Imbalanced Graph Prompt Learning for Online Drug Trafficking Detection

2025 · arXiv (Cornell University)

As the market for illicit drugs remains extremely profitable, major online platforms have become direct-to-consumer intermediaries for illicit drug trafficking participants. These online activities raise significant social concerns that require immediate actions. Existing approaches to …