146 citations · 172 across the 8 of their papers we have counts for
8 papers
HARPA: A Testability-Driven, Literature-Grounded Framework for Research Ideation
Rosni Vasu, Peter Jansen, Pao Siangliulue +4
While there has been a surge of interest in automated scientific discovery (ASD), especially with the emergence of LLMs, it remains challenging for tools to generate hypotheses tha…
Observing Fine-Grained Changes in Jupyter Notebooks During Development Time
Sergey Titov, Konstantin Grotov, Cristina Sarasua +5
In software engineering research, the analysis of fine-grained logs led to significant innovations in areas such as refactoring, security, and code completion. However, even though…
LLM-Based Bot Broadens the Range of Arguments in Online Discussions, Even When Transparently Disclosed as AI
Valeria Vuk, Cristina Sarasua, Fabrizio Gilardi
A wide range of participation is essential for democracy, as it helps prevent the dominance of extreme views, erosion of legitimacy, and political polarization. However, engagement…
HypER: Literature-grounded Hypothesis Generation and Distillation with Provenance
Rosni Vasu, Chandrayee Basu, Bhavana Dalvi Mishra +3
Large Language models have demonstrated promising performance in research ideation across scientific domains. Hypothesis development, the process of generating a highly specific de…
Adaptive political surveys and GPT-4: Tackling the cold start problem with simulated user interactions
Fynn Bachmann, Daan van der Weijden, Lucien Heitz +2
Adaptive questionnaires dynamically select the next question for a survey participant based on their previous answers. Due to digitalisation, they have become a viable alternative…
Fast and Adaptive Questionnaires for Voting Advice Applications
Fynn Bachmann, Cristina Sarasua, Abraham Bernstein
The effectiveness of Voting Advice Applications (VAA) is often compromised by the length of their questionnaires. To address user fatigue and incomplete responses, some application…
Implementations in Machine Ethics: A Survey
Suzanne Tolmeijer, Markus Kneer, Cristina Sarasua +2
Increasingly complex and autonomous systems require machine ethics to maximize the benefits and minimize the risks to society arising from the new technology. It is challenging to…
Non-Parametric Class Completeness Estimators for Collaborative Knowledge Graphs -- The Case of Wikidata
Michael Luggen, Djellel Difallah, Cristina Sarasua +2
Collaborative Knowledge Graph platforms allow humans and automated scripts to collaborate in creating, updating and interlinking entities and facts. To ensure both the completeness…