5 papers
The Potential and Limitations of Vision-Language Models for Human Motion Understanding: A Case Study in Data-Driven Stroke Rehabilitation
Victor Li, Naveenraj Kamalakannan, Avinash Parnandi +2
Vision-language models (VLMs) have demonstrated remarkable performance across a wide range of computer-vision tasks, sparking interest in their potential for digital health applica…
ChatGPT Doesn't Trust Chargers Fans: Guardrail Sensitivity in Context
Victoria R. Li, Yida Chen, Naomi Saphra
While the biases of language models in production are extensively documented, the biases of their guardrails have been neglected. This paper studies how contextual information abou…
Does visualization help AI understand data?
Victoria R. Li, Johnathan Sun, Martin Wattenberg
Charts and graphs help people analyze data, but can they also be useful to AI systems? To investigate this question, we perform a series of experiments with two commercial vision-l…
Can Interpretation Predict Behavior on Unseen Data?
Victoria R. Li, Jenny Kaufmann, Martin Wattenberg +3
Interpretability research often predicts model responses to targeted mechanistic interventions. But can we predict responses to unseen input data? We propose and demonstrate this a…
LAVID: An Agentic LVLM Framework for Diffusion-Generated Video Detection
Qingyuan Liu, Yun-Yun Tsai, Ruijian Zha +4
The impressive achievements of generative models in creating high-quality videos have raised concerns about digital integrity and privacy vulnerabilities. Recent works of AI-genera…