57 papers · 1 filter
: Decision-Targeted Digital Twins
Harry Amad, Mihaela van der Schaar
A digital twin (DT) is a virtual model of a real-world system that can assist decision-making by simulating scenarios induced by different policies. However, typical machine learni…
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…
Recursive Scaling in Masked Diffusion Models
Alba Carballo-Castro, Julianna Piskorz, Paulius Rauba +2
Masked diffusion models (MDMs) have recently emerged as a promising paradigm for sequence generation. Scaling MDMs is conventionally achieved by increasing the parameter count or t…
Fact-Augmented Lookahead Planning for LLM Agents
Samuel Holt, Max Ruiz Luyten, Thomas Pouplin +1
Large Language Models (LLMs) are increasingly capable, but LLM agents still struggle to plan effectively in interactive, partially observable, long-horizon environments when search…
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…
Fast Generalization after Interpolation via Critically Damped Momentum Optimization
Luca Muscarnera, Silas Ruhrberg Estévez, Yuanzhang Xiao +1
A central problem in machine learning is that models can achieve near-perfect training performance while generalizing substantially less well to unseen examples. This gap is especi…