3 papers
cs.AI2026
How Uncertainty Estimation Scales with Sampling in Reasoning Models
Maksym Del, Markus Kängsepp, Marharyta Domnich +4
Uncertainty estimation is critical for deploying reasoning language models, yet remains poorly understood under extended chain-of-thought reasoning. We study parallel sampling as a…
cs.HC2025
Predicting Satisfaction of Counterfactual Explanations from Human Ratings of Explanatory Qualities
Marharyta Domnich, Rasmus Moorits Veski, Julius Välja +2
Counterfactual explanations are a widely used approach in Explainable AI, offering actionable insights into decision-making by illustrating how small changes to input data can lead…
cs.AI2024
Towards Unifying Evaluation of Counterfactual Explanations: Leveraging Large Language Models for Human-Centric Assessments
Marharyta Domnich, Julius Välja, Rasmus Moorits Veski +4
As machine learning models evolve, maintaining transparency demands more human-centric explainable AI techniques. Counterfactual explanations, with roots in human reasoning, identi…