8 papers
From Verification Burden to Trusted Collaboration: Design Goals for LLM-Assisted Literature Reviews
Brenda Nogueira, Werner Geyer, Andrew Anderson +4
Large Language Models (LLMs) are increasingly embedded in academic writing practices. Although numerous studies have explored how researchers employ these tools for scientific writ…
Beyond Permissions: Investigating Mobile Personalization with Simulated Personas
Ibrahim Khalilov, Chaoran Chen, Ziang Xiao +3
Mobile applications increasingly rely on sensor data to infer user context and deliver personalized experiences. Yet the mechanisms behind this personalization remain opaque to use…
ALLOY: Generating Reusable Agent Workflows from User Demonstration
Jiawen Li, Zheng Ning, Yuan Tian +1
Large language models (LLMs) enable end-users to delegate complex tasks to autonomous agents through natural language. However, prompt-based interaction faces critical limitations:…
GLITTER: An AI-assisted Platform for Material-Grounded Asynchronous Discussion in Flipped Learning
Weirui Peng, Yinuo Yang, Zheng Zhang +1
Flipped classrooms promote active learning by having students engage with materials independently before class, allowing in-class time for collaborative problem-solving. During thi…
AROMA: Mixed-Initiative AI Assistance for Non-Visual Cooking by Grounding Multi-modal Information Between Reality and Videos
Zheng Ning, Leyang Li, Daniel Killough +6
Videos offer rich audiovisual information that can support people in performing activities of daily living (ADLs), but they remain largely inaccessible to blind or low-vision (BLV)…
Leveraging Variation Theory in Counterfactual Data Augmentation for Optimized Active Learning
Simret Araya Gebreegziabher, Kuangshi Ai, Zheng Zhang +2
Active Learning (AL) allows models to learn interactively from user feedback. This paper introduces a counterfactual data augmentation approach to AL, particularly addressing the s…