6 papers · 1 filter
CS-Guide: Leveraging LLMs and Student Reflections to Provide Frequent, Scalable Academic Monitoring Feedback to Computer Science Students
Samuel Jacob Chacko, An-I Andy Wang, Lara Perez-Felkner +3
Computer Science (CS) departments often serve large student populations, making timely academic monitoring and personalized feedback difficult. While the recommended counselor-to-s…
Spatial-ViLT: Enhancing Visual Spatial Reasoning through Multi-Task Learning
Chashi Mahiul Islam, Oteo Mamo, Samuel Jacob Chacko +2
Vision-language models (VLMs) have advanced multimodal reasoning but still face challenges in spatial reasoning for 3D scenes and complex object configurations. To address this, we…
Universal and Transferable Adversarial Attack on Large Language Models Using Exponentiated Gradient Descent
Sajib Biswas, Mao Nishino, Samuel Jacob Chacko +1
As large language models (LLMs) are increasingly deployed in critical applications, ensuring their robustness and safety alignment remains a major challenge. Despite the overall su…
Adversarial Attack on Large Language Models using Exponentiated Gradient Descent
Sajib Biswas, Mao Nishino, Samuel Jacob Chacko +1
As Large Language Models (LLMs) are widely used, understanding them systematically is key to improving their safety and realizing their full potential. Although many models are ali…
DeepSeek on a Trip: Inducing Targeted Visual Hallucinations via Representation Vulnerabilities
Chashi Mahiul Islam, Samuel Jacob Chacko, Preston Horne +1
Multimodal Large Language Models (MLLMs) represent the cutting edge of AI technology, with DeepSeek models emerging as a leading open-source alternative offering competitive perfor…
Mechanistic Understandings of Representation Vulnerabilities and Engineering Robust Vision Transformers
Chashi Mahiul Islam, Samuel Jacob Chacko, Mao Nishino +1
While transformer-based models dominate NLP and vision applications, their underlying mechanisms to map the input space to the label space semantically are not well understood. In…