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most citedHow to Prompt? Opportunities and Challenges of Zero- and Few-Shot Learning for Human-AI Interaction in Creative Applications of Generative Models

96 citations · 367 across the 10 of their papers we have counts for

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Showing 2022 · cs.HCShow all

5 papers · 2 filters

cs.HC2022★ 96 cited

How to Prompt? Opportunities and Challenges of Zero- and Few-Shot Learning for Human-AI Interaction in Creative Applications of Generative Models

Hai Dang, Lukas Mecke, Florian Lehmann +2

Deep generative models have the potential to fundamentally change the way we create high-fidelity digital content but are often hard to control. Prompting a generative model is a p…

cs.HC2022★ 87 cited

Beyond Text Generation: Supporting Writers with Continuous Automatic Text Summaries

Hai Dang, Karim Benharrak, Florian Lehmann +1

We propose a text editor to help users plan, structure and reflect on their writing process. It provides continuously updated paragraph-wise summaries as margin annotations, using…

cs.HC2022★ 26 cited

Suggestion Lists vs. Continuous Generation: Interaction Design for Writing with Generative Models on Mobile Devices Affect Text Length, Wording and Perceived Authorship

Florian Lehmann, Niklas Markert, Hai Dang +1

Neural language models have the potential to support human writing. However, questions remain on their integration and influence on writing and output. To address this, we designed…

cs.HC2022★ 6 cited

SummaryLens -- A Smartphone App for Exploring Interactive Use of Automated Text Summarization in Everyday Life

Karim Benharrak, Florian Lehmann, Hai Dang +1

We present SummaryLens, a concept and prototype for a mobile tool that leverages automated text summarization to enable users to quickly scan and summarize physical text documents.…

cs.HC2022★ 39 cited

GANSlider: How Users Control Generative Models for Images using Multiple Sliders with and without Feedforward Information

Hai Dang, Lukas Mecke, Daniel Buschek

We investigate how multiple sliders with and without feedforward visualizations influence users' control of generative models. In an online study (N=138), we collected a dataset of…