1 citations · 1 across the 3 of their papers we have counts for
4 papers
See2Refine: Vision-Language Feedback Improves LLM-Based eHMI Action Designers
Ding Xia, Xinyue Gui, Mark Colley +5
Automated vehicles lack natural communication channels with other road users, making external Human-Machine Interfaces (eHMIs) essential for conveying intent and maintaining trust…
Improving Low-Vision Chart Accessibility via On-Cursor Visual Context
Yotam Sechayk, Hennes Rave, Max Rädler +4
Despite widespread use, charts remain largely inaccessible for Low-Vision Individuals (LVI). Reading charts requires viewing data points within a global context, which is difficult…
Peeking Ahead of the Field Study: Exploring VLM Personas as Support Tools for Embodied Studies in HCI
Xinyue Gui, Ding Xia, Mark Colley +9
Field studies are irreplaceable but costly, time-consuming, and error-prone, which need careful preparation. Inspired by rapid-prototyping in manufacturing, we propose a fast, low-…
HealthGenie: Empowering Users with Healthy Dietary Guidance through Knowledge Graph and Large Language Models
Fan Gao, Xinjie Zhao, Ding Xia +6
Seeking dietary guidance often requires navigating complex professional knowledge while accommodating individual health conditions. Knowledge Graphs (KGs) offer structured and inte…