90 citations · 158 across the 6 of their papers we have counts for
6 papers
How Do Analysts Understand and Verify AI-Assisted Data Analyses?
Ken Gu, Ruoxi Shang, Tim Althoff +2
Data analysis is challenging as it requires synthesizing domain knowledge, statistical expertise, and programming skills. Assistants powered by large language models (LLMs), such a…
On the Design of AI-powered Code Assistants for Notebooks
Andrew M. McNutt, Chenglong Wang, Robert A. DeLine +1
AI-powered code assistants, such as Copilot, are quickly becoming a ubiquitous component of contemporary coding contexts. Among these environments, computational notebooks, such as…
Collecting and Characterizing Natural Language Utterances for Specifying Data Visualizations
Arjun Srinivasan, Nikhila Nyapathy, Bongshin Lee +2
Natural language interfaces (NLIs) for data visualization are becoming increasingly popular both in academic research and in commercial software. Yet, there is a lack of empirical…
Data Visceralization: Enabling Deeper Understanding of Data Using Virtual Reality
Benjamin Lee, Dave Brown, Bongshin Lee +3
A fundamental part of data visualization is transforming data to map abstract information onto visual attributes. While this abstraction is a powerful basis for data visualization,…
InChorus: Designing Consistent Multimodal Interactions for Data Visualization on Tablet Devices
Arjun Srinivasan, Bongshin Lee, Nathalie Henry Riche +2
While tablet devices are a promising platform for data visualization, supporting consistent interactions across different types of visualizations on tablets remains an open challen…
A System for Real-Time Interactive Analysis of Deep Learning Training
Shital Shah, Roland Fernandez, Steven Drucker
Performing diagnosis or exploratory analysis during the training of deep learning models is challenging but often necessary for making a sequence of decisions guided by the increme…