19 citations · 33 across the 5 of their papers we have counts for
5 papers
Misaligned Roles, Misplaced Images: Structural Input Perturbations Expose Multimodal Alignment Blind Spots
Erfan Shayegani, G M Shahariar, Sara Abdali +3
Multimodal Language Models (MMLMs) typically undergo post-training alignment to prevent harmful content generation. However, these alignment stages focus primarily on the assistant…
Can LLMs be Fooled? Investigating Vulnerabilities in LLMs
Sara Abdali, Jia He, CJ Barberan +1
The advent of Large Language Models (LLMs) has garnered significant popularity and wielded immense power across various domains within Natural Language Processing (NLP). While thei…
Securing Large Language Models: Threats, Vulnerabilities and Responsible Practices
Sara Abdali, Richard Anarfi, CJ Barberan +2
Large language models (LLMs) have significantly transformed the landscape of Natural Language Processing (NLP). Their impact extends across a diverse spectrum of tasks, revolutioni…
Decoding the AI Pen: Techniques and Challenges in Detecting AI-Generated Text
Sara Abdali, Richard Anarfi, CJ Barberan +1
Large Language Models (LLMs) have revolutionized the field of Natural Language Generation (NLG) by demonstrating an impressive ability to generate human-like text. However, their w…
Extracting Self-Consistent Causal Insights from Users Feedback with LLMs and In-context Learning
Sara Abdali, Anjali Parikh, Steve Lim +1
Microsoft Windows Feedback Hub is designed to receive customer feedback on a wide variety of subjects including critical topics such as power and battery. Feedback is one of the mo…