13 citations · 36 across the 6 of their papers we have counts for
6 papers
Mobile Fitting Room: On-device Virtual Try-on via Diffusion Models
Justin Blalock, David Munechika, Harsha Karanth +4
The growing digital landscape of fashion e-commerce calls for interactive and user-friendly interfaces for virtually trying on clothes. Traditional try-on methods grapple with chal…
Wordflow: Social Prompt Engineering for Large Language Models
Zijie J. Wang, Aishwarya Chakravarthy, David Munechika +1
Large language models (LLMs) require well-crafted prompts for effective use. Prompt engineering, the process of designing prompts, is challenging, particularly for non-experts who…
SuperNOVA: Design Strategies and Opportunities for Interactive Visualization in Computational Notebooks
Zijie J. Wang, David Munechika, Seongmin Lee +1
Computational notebooks, such as Jupyter Notebook, have become data scientists' de facto programming environments. Many visualization researchers and practitioners have developed i…
DiffusionDB: A Large-scale Prompt Gallery Dataset for Text-to-Image Generative Models
Zijie J. Wang, Evan Montoya, David Munechika +3
With recent advancements in diffusion models, users can generate high-quality images by writing text prompts in natural language. However, generating images with desired details re…
Visual Auditor: Interactive Visualization for Detection and Summarization of Model Biases
David Munechika, Zijie J. Wang, Jack Reidy +4
As machine learning (ML) systems become increasingly widespread, it is necessary to audit these systems for biases prior to their deployment. Recent research has developed algorith…
NOVA: A Practical Method for Creating Notebook-Ready Visual Analytics
Zijie J. Wang, David Munechika, Seongmin Lee +1
How can we develop visual analytics (VA) tools that can be easily adopted? Visualization researchers have developed a large number of web-based VA tools to help data scientists in…