8 papers
ASAP: Visual Analytics for Identifying and Analyzing Image Patterns in AI-generated Images
Jinbin Huang, Yuki Ueno, Chen Chen +4
Generative image models can produce highly realistic images, raising concerns about potential misuse in creating deceptive content. Current deepfake approaches face several challen…
Harnessing LLMs Without Surrendering Control: Delegation Boundaries in Visual Data Storytelling Authoring
Zhuojun Jiang, Yuki Ueno, Chris Bryan
Despite the emergence of large language models (LLMs) for visual data storytelling workflows, there are open questions about how authors decide what activities or tasks to entrust…
VisCanvas: A Node-Based Interface for Exploratory Visualization Authoring with LLMs
Yuki Ueno, Bretho Danzy, Zhuojun Jiang +1
Visual data analysis involves both open-ended exploration and targeted question answering. Visualization authoring tools support this process by enabling users to create visualizat…
Mind Drifts, Data Shifts: Utilizing Mind Wandering to Track the Evolution of User Experience with Data Visualizations
Anjana Arunkumar, Lace Padilla, Chris Bryan
User experience in data visualization is typically assessed through post-viewing self-reports, but these overlook the dynamic cognitive processes during interaction. This study exp…
Defogger: A Visual Analysis Approach for Data Exploration of Sensitive Data Protected by Differential Privacy
Xumeng Wang, Shuangcheng Jiao, Chris Bryan
Differential privacy ensures the security of individual privacy but poses challenges to data exploration processes because the limited privacy budget incapacitates the flexibility…
InFiConD: Interactive No-code Fine-tuning with Concept-based Knowledge Distillation
Jinbin Huang, Wenbin He, Liang Gou +2
The emergence of large-scale pre-trained models has heightened their application in various downstream tasks, yet deployment is a challenge in environments with limited computation…
ASAP: Interpretable Analysis and Summarization of AI-generated Image Patterns at Scale
Jinbin Huang, Chen Chen, Aditi Mishra +3
Generative image models have emerged as a promising technology to produce realistic images. Despite potential benefits, concerns grow about its misuse, particularly in generating d…
InterVLS: Interactive Model Understanding and Improvement with Vision-Language Surrogates
Jinbin Huang, Wenbin He, Liang Gou +2
Deep learning models are widely used in critical applications, highlighting the need for pre-deployment model understanding and improvement. Visual concept-based methods, while inc…