6 papers
Beyond Visual Perception: Insights from Smartphone Interaction of Visually Impaired Users with Large Multimodal Models
Jingyi Xie, Rui Yu, He Zhang +3
Large multimodal models (LMMs) have enabled new AI-powered applications that help people with visual impairments (PVI) receive natural language descriptions of their surroundings t…
Enhancing the Travel Experience for People with Visual Impairments through Multimodal Interaction: NaviGPT, A Real-Time AI-Driven Mobile Navigation System
He Zhang, Nicholas J. Falletta, Jingyi Xie +4
Assistive technologies for people with visual impairments (PVI) have made significant advancements, particularly with the integration of artificial intelligence (AI) and real-time…
When Qualitative Research Meets Large Language Model: Exploring the Potential of QualiGPT as a Tool for Qualitative Coding
He Zhang, Chuhao Wu, Jingyi Xie +5
Qualitative research, renowned for its in-depth exploration of complex phenomena, often involves time-intensive analysis, particularly during the coding stage. Existing software fo…
The Future of Learning: Large Language Models through the Lens of Students
He Zhang, Jingyi Xie, Chuhao Wu +3
As Large-Scale Language Models (LLMs) continue to evolve, they demonstrate significant enhancements in performance and an expansion of functionalities, impacting various domains, i…
Emerging Practices for Large Multimodal Model (LMM) Assistance for People with Visual Impairments: Implications for Design
Jingyi Xie, Rui Yu, He Zhang +3
People with visual impairments perceive their environment non-visually and often use AI-powered assistive tools to obtain textual descriptions of visual information. Recent large v…
Redefining Qualitative Analysis in the AI Era: Utilizing ChatGPT for Efficient Thematic Analysis
He Zhang, Chuhao Wu, Jingyi Xie +3
AI tools, particularly large-scale language model (LLM) based applications such as ChatGPT, have the potential to simplify qualitative research. Through semi-structured interviews…