7 papers
Causal methods for LLM development and evaluation
Dennis Frauen, Marie Brockschmidt, Konstantin Hess +10
Large language model (LLM) development is currently driven by large-scale empirical iteration over data mixtures, reward models, routing strategies, and evaluation pipelines. Here,…
Predicting Startup Success Using Large Language Models: A Novel In-Context Learning Approach
Abdurahman Maarouf, Alket Bakiaj, Stefan Feuerriegel
Venture capital (VC) investments in early-stage startups that end up being successful can yield high returns. However, predicting early-stage startup success remains challenging du…
Beyond Means: A Dynamic Framework for Predicting Customer Satisfaction
Christof Naumzik, Abdurahman Maarouf, Stefan Feuerriegel +1
Online ratings influence customer decision-making, yet standard aggregation methods, such as the sample mean, fail to adapt to quality changes over time and ignore review heterogen…
Analyzing User Characteristics of Hate Speech Spreaders on Social Media
Dominique Geissler, Abdurahman Maarouf, Stefan Feuerriegel
Hate speech on social media threatens the mental and physical well-being of individuals and contributes to real-world violence. Resharing is an important driver behind the spread o…
Generative AI may backfire for counterspeech
Dominik Bär, Abdurahman Maarouf, Stefan Feuerriegel
Online hate speech poses a serious threat to individual well-being and societal cohesion. A promising solution to curb online hate speech is counterspeech. Counterspeech is aimed a…
HQP: A Human-Annotated Dataset for Detecting Online Propaganda
Abdurahman Maarouf, Dominik Bär, Dominique Geissler +1
Online propaganda poses a severe threat to the integrity of societies. However, existing datasets for detecting online propaganda have a key limitation: they were annotated using w…