74 citations · 171 across the 12 of their papers we have counts for
12 papers
Deep Sketch-Based 3D Modeling: A Survey
Alberto Tono, Jiajun Wu, Gordon Wetzstein +4
In the past decade, advances in artificial intelligence have revolutionized sketch-based 3D modeling, leading to a new paradigm known as Deep Sketch-Based 3D Modeling (DS-3DM). DS-…
Script&Shift: A Layered Interface Paradigm for Integrating Content Development and Rhetorical Strategy with LLM Writing Assistants
Momin Siddiqui, Roy Pea, Hari Subramonyam
Good writing is a dynamic process of knowledge transformation, where writers refine and evolve ideas through planning, translating, and reviewing. Generative AI-powered writing too…
Leveraging Large Language Models to Enhance Domain Expert Inclusion in Data Science Workflows
Jasmine Y. Shih, Vishal Mohanty, Yannis Katsis +1
Domain experts can play a crucial role in guiding data scientists to optimize machine learning models while ensuring contextual relevance for downstream use. However, in current wo…
Why and When LLM-Based Assistants Can Go Wrong: Investigating the Effectiveness of Prompt-Based Interactions for Software Help-Seeking
Anjali Khurana, Hari Subramonyam, Parmit K Chilana
Large Language Model (LLM) assistants, such as ChatGPT, have emerged as potential alternatives to search methods for helping users navigate complex, feature-rich software. LLMs use…
Prototyping with Prompts: Emerging Approaches and Challenges in Generative AI Design for Collaborative Software Teams
Hari Subramonyam, Divy Thakkar, Andrew Ku +2
Generative AI models are increasingly being integrated into human task workflows, enabling the production of expressive content across a wide range of contexts. Unlike traditional…
AINeedsPlanner: A Workbook to Support Effective Collaboration Between AI Experts and Clients
Dae Hyun Kim, Hyungyu Shin, Shakhnozakhon Yadgarova +3
Clients often partner with AI experts to develop AI applications tailored to their needs. In these partnerships, careful planning and clear communication are critical, as inaccurat…
Is a Seat at the Table Enough? Engaging Teachers and Students in Dataset Specification for ML in Education
Mei Tan, Hansol Lee, Dakuo Wang +1
Despite the promises of ML in education, its adoption in the classroom has surfaced numerous issues regarding fairness, accountability, and transparency, as well as concerns about…
More than Model Documentation: Uncovering Teachers' Bespoke Information Needs for Informed Classroom Integration of ChatGPT
Mei Tan, Hariharan Subramonyam
ChatGPT has entered classrooms, but not via the typical route of other educational technology, which includes comprehensive training, documentation, and vetting. Consequently, teac…
Bridging the Gulf of Envisioning: Cognitive Design Challenges in LLM Interfaces
Hariharan Subramonyam, Roy Pea, Christopher Lawrence Pondoc +2
Large language models (LLMs) exhibit dynamic capabilities and appear to comprehend complex and ambiguous natural language prompts. However, calibrating LLM interactions is challeng…
Are We Closing the Loop Yet? Gaps in the Generalizability of VIS4ML Research
Hariharan Subramonyam, Jessica Hullman
Visualization for machine learning (VIS4ML) research aims to help experts apply their prior knowledge to develop, understand, and improve the performance of machine learning models…
Spellburst: A Node-based Interface for Exploratory Creative Coding with Natural Language Prompts
Tyler Angert, Miroslav Ivan Suzara, Jenny Han +2
Creative coding tasks are often exploratory in nature. When producing digital artwork, artists usually begin with a high-level semantic construct such as a "stained glass filter" a…
fAIlureNotes: Supporting Designers in Understanding the Limits of AI Models for Computer Vision Tasks
Steven Moore, Q. Vera Liao, Hariharan Subramonyam
To design with AI models, user experience (UX) designers must assess the fit between the model and user needs. Based on user research, they need to contextualize the model's behavi…