10 papers
Probabilistic Residual Learning for Online Recommendations
Wenyuan Wang, Yusong Zhao, Zihao Xu +11
Modern recommender systems are typically based on deep learning (DL) models, where a dense encoder learns representations of users and items. As a result, these systems often suffe…
EditLord: Learning Code Transformation Rules for Code Editing
Weichen Li, Albert Jan, Baishakhi Ray +3
Code editing is a foundational task in software development, where its effectiveness depends on whether it introduces desired code property changes without changing the original co…
Diversity Helps Jailbreak Large Language Models
Weiliang Zhao, Daniel Ben-Levi, Wei Hao +2
We have uncovered a powerful jailbreak technique that leverages large language models' ability to diverge from prior context, enabling them to bypass safety constraints and generat…
LAVID: An Agentic LVLM Framework for Diffusion-Generated Video Detection
Qingyuan Liu, Yun-Yun Tsai, Ruijian Zha +4
The impressive achievements of generative models in creating high-quality videos have raised concerns about digital integrity and privacy vulnerabilities. Recent works of AI-genera…
Learning to Rewrite: Generalized LLM-Generated Text Detection
Ran Li, Wei Hao, Weiliang Zhao +2
Large language models (LLMs) present significant risks when used to generate non-factual content and spread disinformation at scale. Detecting such LLM-generated content is crucial…
I Can Hear You: Selective Robust Training for Deepfake Audio Detection
Zirui Zhang, Wei Hao, Aroon Sankoh +4
Recent advances in AI-generated voices have intensified the challenge of detecting deepfake audio, posing risks for scams and the spread of disinformation. To tackle this issue, we…