1 citations · 1 across the 6 of their papers we have counts for
8 papers
Human-AI Collaboration in Radiology: The Case of Pulmonary Embolism
Paul Goldsmith-Pinkham, Chenhao Tan, Alexander K. Zentefis
We study how radiologists use AI to diagnose pulmonary embolism (PE), tracking over 100,000 scans interpreted by nearly 400 radiologists during the staggered rollout of a real-worl…
Know Thyself? On the Incapability and Implications of AI Self-Recognition
Xiaoyan Bai, Aryan Shrivastava, Ari Holtzman +1
Self-recognition is a crucial metacognitive capability for AI systems, relevant not only for psychological analysis but also for safety, particularly in evaluative scenarios. Motiv…
Why Can't Transformers Learn Multiplication? Reverse-Engineering Reveals Long-Range Dependency Pitfalls
Xiaoyan Bai, Itamar Pres, Yuntian Deng +5
Language models are increasingly capable, yet still fail at a seemingly simple task of multi-digit multiplication. In this work, we study why, by reverse-engineering a model that s…
MoVa: Towards Generalizable Classification of Human Morals and Values
Ziyu Chen, Junfei Sun, Chenxi Li +6
Identifying human morals and values embedded in language is essential to empirical studies of communication. However, researchers often face substantial difficulty navigating the d…
Prompting as Scientific Inquiry
Ari Holtzman, Chenhao Tan
Prompting is the primary method by which we study and control large language models. It is also one of the most powerful: nearly every major capability attributed to LLMs-few-shot…
"I Cannot Write This Because It Violates Our Content Policy": Understanding Content Moderation Policies and User Experiences in Generative AI Products
Lan Gao, Oscar Chen, Rachel Lee +3
While recent research has focused on developing safeguards for generative AI (GAI) model-level content safety, little is known about how content moderation to prevent malicious con…