14 papers
When Style Breaks Safety: Defending LLMs Against Superficial Style Alignment
Yuxin Xiao, Sana Tonekaboni, Walter Gerych +2
Large language models (LLMs) can be prompted with specific styles (e.g., formatting responses as lists), including in malicious queries. Prior jailbreak research mainly augments th…
Robustness Beyond Known Groups with Low-rank Adaptation
Abinitha Gourabathina, Hyewon Jeong, Teya Bergamaschi +2
Deep learning models trained to optimize average accuracy often exhibit systematic failures on particular subpopulations. In real world settings, the subpopulations most affected b…
Explainable AI as a Double-Edged Sword in Dermatology: The Impact on Clinicians versus The Public
Xuhai Xu, Haoyu Hu, Haoran Zhang +21
Artificial intelligence (AI) is increasingly permeating healthcare, from physician assistants to consumer applications. Since AI algorithm's opacity challenges human interaction, e…
Personalizing Prostate Cancer Education for Patients Using an EHR-Integrated LLM Agent
Yuexing Hao, Jason Holmes, Mark R. Waddle +10
Cancer patients often lack timely education and personalized support due to clinician workload. This quality improvement study develops and evaluates a Large Language Model (LLM) a…
Aggregation Hides Out-of-Distribution Generalization Failures from Spurious Correlations
Olawale Salaudeen, Haoran Zhang, Kumail Alhamoud +2
Benchmarks for out-of-distribution (OOD) generalization frequently show a strong positive correlation between in-distribution (ID) and OOD accuracy across models, termed "accuracy-…
KScope: A Framework for Characterizing the Knowledge Status of Language Models
Yuxin Xiao, Shan Chen, Jack Gallifant +3
Characterizing a large language model's (LLM's) knowledge of a given question is challenging. As a result, prior work has primarily examined LLM behavior under knowledge conflicts,…