165 citations · 580 across the 15 of their papers we have counts for
15 papers
Collaborative Document Editing with Multiple Users and AI Agents
Florian Lehmann, Krystsina Shauchenka, Daniel Buschek
Current AI writing support tools are largely designed for individuals, complicating collaboration when co-writers must leave the shared workspace to use AI and then communicate and…
StudyAlign: A Software System for Conducting Web-Based User Studies with Functional Interactive Prototypes
Florian Lehmann, Daniel Buschek
Interactive systems are commonly prototyped as web applications. This approach enables studies with functional prototypes on a large scale. However, setting up these studies can be…
Exploring Mobile Touch Interaction with Large Language Models
Tim Zindulka, Jannek Sekowski, Florian Lehmann +1
Interacting with Large Language Models (LLMs) for text editing on mobile devices currently requires users to break out of their writing environment and switch to a conversational A…
Content-Driven Local Response: Supporting Sentence-Level and Message-Level Mobile Email Replies With and Without AI
Tim Zindulka, Sven Goller, Florian Lehmann +1
Mobile emailing demands efficiency in diverse situations, which motivates the use of AI. However, generated text does not always reflect how people want to respond. This challenges…
Functional Flexibility in Generative AI Interfaces: Text Editing with LLMs through Conversations, Toolbars, and Prompts
Florian Lehmann, Daniel Buschek
Prompting-based user interfaces (UIs) shift the task of defining and accessing relevant functions from developers to users. However, how UIs shape this flexibility has not yet been…
Writer-Defined AI Personas for On-Demand Feedback Generation
Karim Benharrak, Tim Zindulka, Florian Lehmann +2
Compelling writing is tailored to its audience. This is challenging, as writers may struggle to empathize with readers, get feedback in time, or gain access to the target group. We…
Choice Over Control: How Users Write with Large Language Models using Diegetic and Non-Diegetic Prompting
Hai Dang, Sven Goller, Florian Lehmann +1
We propose a conceptual perspective on prompts for Large Language Models (LLMs) that distinguishes between (1) diegetic prompts (part of the narrative, e.g. "Once upon a time, I sa…
The AI Ghostwriter Effect: When Users Do Not Perceive Ownership of AI-Generated Text But Self-Declare as Authors
Fiona Draxler, Anna Werner, Florian Lehmann +4
Human-AI interaction in text production increases complexity in authorship. In two empirical studies (n1 = 30 & n2 = 96), we investigate authorship and ownership in human-AI collab…
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…
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…
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…
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.…
Examining Autocompletion as a Basic Concept for Interaction with Generative AI
Florian Lehmann, Daniel Buschek
Autocompletion is an approach that extends and continues partial user input. We propose to interpret autocompletion as a basic interaction concept in human-AI interaction. We first…
Nine Potential Pitfalls when Designing Human-AI Co-Creative Systems
Daniel Buschek, Lukas Mecke, Florian Lehmann +1
This position paper examines potential pitfalls on the way towards achieving human-AI co-creation with generative models in a way that is beneficial to the users' interests. In par…
Heartbeats in the Wild: A Field Study Exploring ECG Biometrics in Everyday Life
Florian Lehmann, Daniel Buschek
This paper reports on an in-depth study of electrocardiogram (ECG) biometrics in everyday life. We collected ECG data from 20 people over a week, using a non-medical chest tracker.…