Florian Lehmann

Florian Lehmann
University of Bayreuth · Department of Computer Science

Master of Science

About

13
Publications
936
Reads
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38
Citations
Citations since 2016
13 Research Items
38 Citations
201620172018201920202021202202468101214
201620172018201920202021202202468101214
201620172018201920202021202202468101214
201620172018201920202021202202468101214

Publications

Publications (13)
Preprint
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 promising recent development that in principle enables end-users to creatively leverage zero-shot and few-shot learning to assign new tasks to an AI ad-hoc, simply by writ...
Preprint
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 understand how users interact wit...
Preprint
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 and compared two user interfaces for writing with AI on mobile devices, which manipulate levels of initiative and control: 1) Writing with continuously generated text, t...
Preprint
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. We further combine this with a text-to-speech system to read out the summary on demand. With this concept, we propose and explore a concrete application case of bringing...
Preprint
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 describe the concept of autocompletion and dissect its user interface and interaction elements, using the well-established textual autocompletion in search engines as an...
Preprint
Full-text available
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 particular, we collected a set of nine potential pitfalls, based on the literature and our own experiences as researchers working at the intersection of HCI and AI. We illus...
Article
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 describe the concept of autocompletion and dissect its user interface and interaction elements, using the well-established textual autocompletion in search engines as an...
Preprint
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. We evaluated user identification accuracy in several scenarios and observed equal error rates of 9.15% to 21.91%, heavily depending on 1) the number of days used for tra...
Conference Paper
Full-text available
We argue that future mobile interfaces should differentiate between various contextual factors like grip and active fingers, adjusting screen elements and behaviors automatically, thus moving from merely responsive design to responsive interaction. Toward this end we conducted a systematic study of screen taps on a mobile device to find out how the...
Article
The increasing usage of new technologies implies changes for personality research. First, human behavior becomes measurable by digital data, and second, digital manifestations to some extent replace conventional behavior in the analog world. This offers the opportunity to investigate personality traits by means of digital footprints. In this contex...
Conference Paper
Full-text available
Reducing workload in a UI while still letting users feel in control is not trivial. This workload/control tradeoff is described in the literature and deserves attention in design practice. However, there is no evaluation framework for it supporting both explicit and implicit measurement, mainly because measuring sense of control implicitly is just...

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Projects

Project (1)
Project
Try to identify and study the various factors that impact the performance (and precision and error rate) of touch interactions. While the starting point for analysis is Fitts' Law, the general goal is to extend or modify Fitts' Law according to the empirical results. Context factors are: regions on the screen, direction of movement, and hand grip (for mobile devices).