6 papers
Taming Data Challenges in ML-based Security Tasks Using Generative AI
Shravya Kanchi, Neal Mangaokar, Aravind Cheruvu +4
Machine learning-based supervised classifiers are widely used for security tasks, and their improvement has been largely focused on algorithmic advancements. We argue that data cha…
Optimus: A Robust Defense Framework for Mitigating Toxicity while Fine-Tuning Conversational AI
Aravind Cheruvu, Shravya Kanchi, Sifat Muhammad Abdullah +4
Customizing Large Language Models (LLMs) on untrusted datasets poses severe risks of injecting toxic behaviors. In this work, we introduce Optimus, a novel defense framework design…
Off-The-Shelf Image-to-Image Models Are All You Need To Defeat Image Protection Schemes
Xavier Pleimling, Sifat Muhammad Abdullah, Gunjan Balde +4
Advances in Generative AI (GenAI) have led to the development of various protection strategies to prevent the unauthorized use of images. These methods rely on adding imperceptible…
Prompt and Circumstances: Evaluating the Efficacy of Human Prompt Inference in AI-Generated Art
Khoi Trinh, Scott Seidenberger, Joseph Spracklen +4
The emerging field of AI-generated art has witnessed the rise of prompt marketplaces, where creators can purchase, sell, or share prompts to generate unique artworks. These marketp…
We Have a Package for You! A Comprehensive Analysis of Package Hallucinations by Code Generating LLMs
Joseph Spracklen, Raveen Wijewickrama, A H M Nazmus Sakib +3
The reliance of popular programming languages such as Python and JavaScript on centralized package repositories and open-source software, combined with the emergence of code-genera…
Promptly Yours? A Human Subject Study on Prompt Inference in AI-Generated Art
Khoi Trinh, Joseph Spracklen, Raveen Wijewickrama +3
The emerging field of AI-generated art has witnessed the rise of prompt marketplaces, where creators can purchase, sell, or share prompts for generating unique artworks. These mark…