Search Results for author: Daniel Buschek

Found 15 papers, 0 papers with code

Deceptive Patterns of Intelligent and Interactive Writing Assistants

no code implementations14 Apr 2024 Karim Benharrak, Tim Zindulka, Daniel Buschek

Large Language Models have become an integral part of new intelligent and interactive writing assistants.


Writer-Defined AI Personas for On-Demand Feedback Generation

no code implementations19 Sep 2023 Karim Benharrak, Tim Zindulka, Florian Lehmann, Hendrik Heuer, Daniel Buschek

This is challenging, as writers may struggle to empathize with readers, get feedback in time, or gain access to the target group.

The AI Ghostwriter Effect: When Users Do Not Perceive Ownership of AI-Generated Text But Self-Declare as Authors

no code implementations6 Mar 2023 Fiona Draxler, Anna Werner, Florian Lehmann, Matthias Hoppe, Albrecht Schmidt, Daniel Buschek, Robin Welsch

Participants were more likely to attribute ownership to supposedly human ghostwriters than AI ghostwriters, resulting in a higher ownership-authorship discrepancy for human ghostwriters.

Attribute Text Generation

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

no code implementations6 Mar 2023 Hai Dang, Sven Goller, Florian Lehmann, Daniel Buschek

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.").

Co-Writing with Opinionated Language Models Affects Users' Views

no code implementations1 Feb 2023 Maurice Jakesch, Advait Bhat, Daniel Buschek, Lior Zalmanson, Mor Naaman

Using the opinionated language model affected the opinions expressed in participants' writing and shifted their opinions in the subsequent attitude survey.

Language Modelling

Beyond Text Generation: Supporting Writers with Continuous Automatic Text Summaries

no code implementations19 Aug 2022 Hai Dang, Karim Benharrak, Florian Lehmann, Daniel Buschek

As a key finding, the summaries gave users an external perspective on their writing and helped them to revise the content and scope of their drafted paragraphs.

Text Generation Text Summarization

CharacterChat: Supporting the Creation of Fictional Characters through Conversation and Progressive Manifestation with a Chatbot

no code implementations23 Jun 2021 Oliver Schmitt, Daniel Buschek

We iteratively developed CharacterChat in a user-centred approach, starting with a survey on character creation with writers (N=30), followed by two qualitative user studies (N=7 and N=8).

Chatbot Language Modelling

Nine Potential Pitfalls when Designing Human-AI Co-Creative Systems

no code implementations1 Apr 2021 Daniel Buschek, Lukas Mecke, Florian Lehmann, Hai Dang

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.


The Impact of Multiple Parallel Phrase Suggestions on Email Input and Composition Behaviour of Native and Non-Native English Writers

no code implementations22 Jan 2021 Daniel Buschek, Martin Zürn, Malin Eiband

We present an in-depth analysis of the impact of multi-word suggestion choices from a neural language model on user behaviour regarding input and text composition in email writing.

Language Modelling

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