2 citations · 2 across the 1 of their papers we have counts for
5 papers
Can Reinforcement Learning Unlock the Hidden Dangers in Aligned Large Language Models?
Mohammad Bahrami Karkevandi, Nishant Vishwamitra, Peyman Najafirad
Large Language Models (LLMs) have demonstrated impressive capabilities in natural language tasks, but their safety and morality remain contentious due to their training on internet…
Image Safeguarding: Reasoning with Conditional Vision Language Model and Obfuscating Unsafe Content Counterfactually
Mazal Bethany, Brandon Wherry, Nishant Vishwamitra +1
Social media platforms are being increasingly used by malicious actors to share unsafe content, such as images depicting sexual activity, cyberbullying, and self-harm. Consequently…
An Investigation of Large Language Models for Real-World Hate Speech Detection
Keyan Guo, Alexander Hu, Jaden Mu +4
Hate speech has emerged as a major problem plaguing our social spaces today. While there have been significant efforts to address this problem, existing methods are still significa…
Deciphering Textual Authenticity: A Generalized Strategy through the Lens of Large Language Semantics for Detecting Human vs. Machine-Generated Text
Mazal Bethany, Brandon Wherry, Emet Bethany +3
With the recent proliferation of Large Language Models (LLMs), there has been an increasing demand for tools to detect machine-generated text. The effective detection of machine-ge…
Understanding and Measuring Robustness of Multimodal Learning
Nishant Vishwamitra, Hongxin Hu, Ziming Zhao +2
The modern digital world is increasingly becoming multimodal. Although multimodal learning has recently revolutionized the state-of-the-art performance in multimodal tasks, relativ…