activity
20222024
most citedWhy and When LLM-Based Assistants Can Go Wrong: Investigating the Effectiveness of Prompt-Based Interactions for Software Help-Seeking

74 citations · 174 across the 9 of their papers we have counts for

collaborators

9 papers

cs.HC202474 cited

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…

cs.CY20232 cited

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…

cs.HC20233 cited

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…

cs.HC2023

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…

cs.SE202371 cited

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…

cs.LG20234 cited

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…