5 citations · 5 across the 3 of their papers we have counts for
10 papers
TextCloak: Thwarting Unauthorized LLM Exploitation via RL-Driven Unlearnable Text
Chengshuai Zhao, Pingchuan Ma, Dawei Li +4
The rapid development of Large Language Models (LLMs) has led to significant advances across a wide range of language tasks, while simultaneously raising growing concerns about una…
To See is Not to Learn: Protecting Multimodal Data from Unauthorized Fine-Tuning of Large Vision-Language Model
Chengshuai Zhao, Zhen Tan, Dawei Li +2
The rapid advancement of Large Vision-Language Models (LVLMs) is increasingly accompanied by unauthorized scraping and training on multimodal web data, posing severe copyright and…
Is Chain-of-Thought Reasoning of LLMs a Mirage? A Data Distribution Lens
Chengshuai Zhao, Zhen Tan, Pingchuan Ma +5
Chain-of-Thought (CoT) prompting has been shown to be effective in eliciting structured reasoning (i.e., CoT reasoning) from large language models (LLMs). Regardless of its popular…
ToolPRMBench: Evaluating and Advancing Process Reward Models for Tool-using Agents
Dawei Li, Yuguang Yao, Zhen Tan +2
Reward-guided search methods have demonstrated strong potential in enhancing tool-using agents by effectively guiding sampling and exploration over complex action spaces. As a core…
Ontology-Aware RAG for Improved Question-Answering in Cybersecurity Education
Chengshuai Zhao, Garima Agrawal, Fan Zhang +5
Integrating AI into education has the potential to transform the teaching of science and technology courses, particularly in the field of cybersecurity. AI-driven question-answerin…
Who's Your Judge? On the Detectability of LLM-Generated Judgments
Dawei Li, Zhen Tan, Chengshuai Zhao +6
Large Language Model (LLM)-based judgments leverage powerful LLMs to efficiently evaluate candidate content and provide judgment scores. However, the inherent biases and vulnerabil…