5 papers
LLM Ghostbusters: Surgical Hallucination Suppression via Adaptive Unlearning
Joseph Spracklen, Pedram Aghazadeh, Farinaz Koushanfar +1
Hallucinations, outputs that sound plausible but are factually incorrect, remain an open challenge for deployed LLMs. In code generation, models frequently hallucinate non-existent…
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…
To WASM or Not to WASM: Evaluation of Browser Fingerprinting Defenses Under WASM based Obfuscation
A H M Nazmus Sakib, Mahsin Bin Akram, Joseph Spracklen +4
Browser fingerprinting defenses have historically focused on detecting JavaScript(JS)-based tracking techniques. However, the widespread adoption of WebAssembly (WASM) introduces a…
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…