Florian Lehmann

schoolUniversity of Bayreuthbar_chart#1219 Global Rank

Total Papers

HCI Rank

#1219

Research Areas

Years Active

Recent Publications

Collaborative Document Editing with Multiple Users and AI Agents

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 reintegrate results. We propose integrating AI agents directly into collaborative writing environments. Our prototype makes AI use visible…

CHI '253rd AuthorHand Gesture Recognition +1

Exploring Mobile Touch Interaction with Large Language Models

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 AI interface. In this paper, we propose to control the LLM via touch gestures performed directly on the text. We first chart a design space…

CHI '253rd AuthorVoice User Interface (VUI) Design +1

Content-Driven Local Response: Supporting Sentence-Level and Message-Level Mobile Email Replies With and Without AI

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 users with AI involvement tradeoffs not yet considered in email UIs. We address this with a new UI concept called Content-Driven Local Res…

DIS '243rd AuthorGenerative AI (Text, Image, Music, Video) +2

The AI Ghostwriter Effect: When Users do not Perceive Ownership of AI-Generated Text but Self-Declare as Authors

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 collaboration for personalized language generation. We show an AI Ghostwriter Effect: Users do not consider themselves the owners and authors of…

CHI '243rd AuthorGenerative AI (Text, Image, Music, Video) +1

Writer-Defined AI Personas for On-Demand Feedback Generation

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 propose a concept that generates on-demand feedback, based on writer-defined AI personas of any target audience. We explore this concept w…

MOBILEHCI '231st AuthorIntelligent Voice Assistants (Alexa, Siri, etc.) +1

Typing Behavior is About More than Speed: Users' Strategies for Choosing Word Suggestions Despite Slower Typing Rates

Mobile word suggestions can slow down typing, yet are still widely used. To investigate the apparent benefits beyond speed, we analyzed typing behavior of 15,162 users of mobile devices. Controlling for natural typing speed (a confounding factor not considered by prior work), we statistically show that slower typists…

CHI '233rd AuthorHuman-LLM Collaboration +1

Choice Over Control: How Users Write with Large Language Models using Diegetic and Non-Diegetic Prompting

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 saw a fox...”), and (2) non-diegetic prompts (external, e.g. “Write about the adventures of the fox.”). With this lens, we study how 129 crow…

UIST '223rd AuthorHuman-LLM Collaboration +1

Beyond Text Generation: Supporting Writers with Continuous Automatic Text Summaries.

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 automatic text summarization. Summary levels range from full text, to selected (central) sentences, down to a collection of keywords. To un…

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