10 citations · 23 across the 24 of their papers we have counts for
5 papers · 1 filter
Are We in the AI-Generated Text World Already? Quantifying and Monitoring AIGT on Social Media
Zhen Sun, Zongmin Zhang, Xinyue Shen +5
Social media platforms are experiencing a growing presence of AI-Generated Texts (AIGTs). However, the misuse of AIGTs could have profound implications for public opinion, such as…
On the Generalization and Adaptation Ability of Machine-Generated Text Detectors in Academic Writing
Yule Liu, Zhiyuan Zhong, Yifan Liao +8
The rising popularity of large language models (LLMs) has raised concerns about machine-generated text (MGT), particularly in academic settings, where issues like plagiarism and mi…
Quantized Delta Weight Is Safety Keeper
Yule Liu, Zhen Sun, Xinlei He +1
Recent advancements in fine-tuning proprietary language models enable customized applications across various domains but also introduce two major challenges: high resource demands…
PEFTGuard: Detecting Backdoor Attacks Against Parameter-Efficient Fine-Tuning
Zhen Sun, Tianshuo Cong, Yule Liu +5
Fine-tuning is an essential process to improve the performance of Large Language Models (LLMs) in specific domains, with Parameter-Efficient Fine-Tuning (PEFT) gaining popularity d…
Jailbreak Attacks and Defenses Against Large Language Models: A Survey
Sibo Yi, Yule Liu, Zhen Sun +5
Large Language Models (LLMs) have performed exceptionally in various text-generative tasks, including question answering, translation, code completion, etc. However, the over-assis…