39 citations · 76 across the 8 of their papers we have counts for
4 papers · 1 filter
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…
A Fused Large Language Model for Predicting Startup Success
Abdurahman Maarouf, Stefan Feuerriegel, Nicolas Pröllochs
Investors are continuously seeking profitable investment opportunities in startups and, hence, for effective decision-making, need to predict a startup's probability of success. No…