most citedCo-audit: tools to help humans double-check AI-generated content

3 citations · 3 across the 3 of their papers we have counts for

collaborators

5 papers

cs.SE2024

Requirements are All You Need: The Final Frontier for End-User Software Engineering

Diana Robinson, Christian Cabrera, Andrew D. Gordon +2

What if end users could own the software development lifecycle from conception to deployment using only requirements expressed in language, images, video or audio? We explore this…

cs.HC2024

"My toxic trait is thinking I'll remember this": gaps in the learner experience of video tutorials for feature-rich software

Ian Drosos, Advait Sarkar, Andrew D. Gordon

Video tutorials are a popular medium for informal and formal learning. However, when learners attempt to view and follow along with these tutorials, they encounter what we call gap…

cs.PL2024

Solving Data-centric Tasks using Large Language Models

Shraddha Barke, Christian Poelitz, Carina Suzana Negreanu +10

Large language models (LLMs) are rapidly replacing help forums like StackOverflow, and are especially helpful for non-professional programmers and end users. These users are often…

cs.HC2023

Participatory prompting: a user-centric research method for eliciting AI assistance opportunities in knowledge workflows

Advait Sarkar, Ian Drosos, Rob Deline +5

Generative AI, such as image generation models and large language models, stands to provide tremendous value to end-user programmers in creative and knowledge workflows. Current re…

cs.HC20233 cited

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…