2 papers
cs.CL2026
Paved with True Intents: Intent-Aware Training Improves LLM Safety Classification Across Training Regimes
Jeremias Ferrao, Niclas Müller-Hof, Iustin Sîrbu +2
We argue that safety classifiers should model user intent as an explicit signal between the prompt and the final label. To study this, we introduce AIMS, a human-annotated dataset…
stat.ML2025
Evaluating Uncertainty in Deep Gaussian Processes
Matthijs van der Lende, Jeremias Lino Ferrao, Niclas Müller-Hof
Reliable uncertainty estimates are crucial in modern machine learning. Deep Gaussian Processes (DGPs) and Deep Sigma Point Processes (DSPPs) extend GPs hierarchically, offering pro…