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cs.LG2026
Guiding Posterior Exploration with Optimizer-Derived Geometry
Moritz Schlager, Emanuel Sommer, Thomas Möllenhoff +1
Sampling-based methods offer a principled approach to uncertainty quantification in Bayesian neural networks. Their practical use, however, is often challenged by the computational…
cs.LG2026
MO-CAPO: Multi-Objective Cost-Aware Prompt Optimization
Jan Büssing, Moritz Schlager, Timo Heià +2
Large language models (LLMs) achieve strong performance across a wide range of tasks but are highly sensitive to prompt design, motivating the need for automatic prompt optimizatio…