115 citations · 165 across the 4 of their papers we have counts for
4 papers · 1 filter
Dynamic Prompt Middleware: Contextual Prompt Refinement Controls for Comprehension Tasks
Ian Drosos, Jack Williams, Advait Sarkar +1
Effective prompting of generative AI is challenging for many users, particularly in expressing context for comprehension tasks such as explaining spreadsheet formulas, Python code,…
Improving Steering and Verification in AI-Assisted Data Analysis with Interactive Task Decomposition
Majeed Kazemitabaar, Jack Williams, Ian Drosos +4
LLM-powered tools like ChatGPT Data Analysis, have the potential to help users tackle the challenging task of data analysis programming, which requires expertise in data processing…
Co-audit: tools to help humans double-check AI-generated content
Andrew D. Gordon, Carina Negreanu, José Cambronero +9
Users are increasingly being warned to check AI-generated content for correctness. Still, as LLMs (and other generative models) generate more complex output, such as summaries, tab…
"What It Wants Me To Say": Bridging the Abstraction Gap Between End-User Programmers and Code-Generating Large Language Models
Michael Xieyang Liu, Advait Sarkar, Carina Negreanu +4
Code-generating large language models translate natural language into code. However, only a small portion of the infinite space of naturalistic utterances is effective at guiding c…