29 papers
OncoSynth: Synthetic data generation for treatment effect estimation in oncology
Octavia-Andreea Ciora, Julian Welzel, Dennis Frauen +6
In oncology, access to patient-level data is often restricted. Synthetic data provides an alternative for analyzing treatment effectiveness, but existing methods for synthetic data…
Nonparametric LLM Evaluation from Preference Data
Dennis Frauen, Athiya Deviyani, Mihaela van der Schaar +1
Evaluating the performance of large language models (LLMs) from human preference data is crucial for obtaining LLM leaderboards. However, many existing approaches either rely on re…
Orthogonal Learner for Estimating Heterogeneous Long-Term Treatment Effects
Haorui Ma, Dennis Frauen, Valentyn Melnychuk +1
Estimation of heterogeneous long-term treatment effects (HLTEs) is relevant for personalized decision-making in marketing, economics, and medicine, where short-term observational d…
Rank-Learner: Orthogonal Ranking of Treatment Effects
Henri Arno, Dennis Frauen, Emil Javurek +2
Many decision-making problems require ranking individuals by their treatment effects rather than estimating the exact effect magnitudes. Examples include prioritizing patients for…
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,…
Adaptive Experimentation for Censored Survival Outcomes
Yuxin Wang, Dennis Frauen, Jonas Schweisthal +3
Adaptive experimentation enables efficient estimation of causal effects, but existing methods are not designed for survival data with censoring, where event times are only partiall…