1 citations · 1 across the 4 of their papers we have counts for
4 papers
AutoAdv: Automated Adversarial Prompting for Multi-Turn Jailbreaking of Large Language Models
Aashray Reddy, Andrew Zagula, Nicholas Saban
Large Language Models (LLMs) remain vulnerable to jailbreaking attacks where adversarial prompts elicit harmful outputs. Yet most evaluations focus on single-turn interactions whil…
BabyVLM-V2: Toward Developmentally Grounded Pretraining and Benchmarking of Vision Foundation Models
Shengao Wang, Wenqi Wang, Zecheng Wang +20
Early children's developmental trajectories set up a natural goal for sample-efficient pretraining of vision foundation models. We introduce BabyVLM-V2, a developmentally grounded…
TRACE: AI-Assisted Assessment of Collaborative Projects in Computer Science Education
Songmei Yu, Andrew Zagula
Collaborative group projects are integral to computer science education, fostering teamwork, problem-solving, and industry-relevant skills. However, assessing individual contributi…
AutoAdv: Automated Adversarial Prompting for Multi-Turn Jailbreaking of Large Language Models
Aashray Reddy, Andrew Zagula, Nicholas Saban
Large Language Models (LLMs) continue to exhibit vulnerabilities to jailbreaking attacks: carefully crafted malicious inputs intended to circumvent safety guardrails and elicit har…