4 citations · 10 across the 6 of their papers we have counts for
6 papers
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…
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…
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…
Interpreting the structure of multi-object representations in vision encoders
Tarun Khajuria, Braian Olmiro Dias, Marharyta Domnich +1
In this work, we interpret the representations of multi-object scenes in vision encoders through the lens of structured representations. Structured representations allow modeling o…
COIN: Counterfactual inpainting for weakly supervised semantic segmentation for medical images
Dmytro Shvetsov, Joonas Ariva, Marharyta Domnich +2
Deep learning is dramatically transforming the field of medical imaging and radiology, enabling the identification of pathologies in medical images, including computed tomography (…
Enhancing Counterfactual Explanation Search with Diffusion Distance and Directional Coherence
Marharyta Domnich, Raul Vicente
A pressing issue in the adoption of AI models is the increasing demand for more human-centric explanations of their predictions. To advance towards more human-centric explanations,…