6 citations · 12 across the 16 of their papers we have counts for
3 papers · 2 filters
Human-Readable Adversarial Prompts: An Investigation into LLM Vulnerabilities Using Situational Context
Nilanjana Das, Edward Raff, Aman Chadha +1
As the AI systems become deeply embedded in social media platforms, we've uncovered a concerning security vulnerability that goes beyond traditional adversarial attacks. It becomes…
Towards Robust Evaluation of Unlearning in LLMs via Data Transformations
Abhinav Joshi, Shaswati Saha, Divyaksh Shukla +4
Large Language Models (LLMs) have shown to be a great success in a wide range of applications ranging from regular NLP-based use cases to AI agents. LLMs have been trained on a vas…
Human-Interpretable Adversarial Prompt Attack on Large Language Models with Situational Context
Nilanjana Das, Edward Raff, Manas Gaur
Previous research on testing the vulnerabilities in Large Language Models (LLMs) using adversarial attacks has primarily focused on nonsensical prompt injections, which are easily…