Qualitative Study on Dense-Labeling Model Generalization for Semantic Concept-Augmented Learning and Post-Hoc Analysis for Time Series Classification
Abstract
A qualitative study of dense-labeling model generalization for time-series concept identification on the UCR archive for the paper "Semantic Concept-Augmented Learning and Post-Hoc Analysis for Time Series Classification". This work will be presented at XAI-2026, to be held in Fortaleza, Brazil.
Fields of Study & Subjects
Time Series Analysis and Forecasting
Explainable Artificial Intelligence (XAI)
Domain Adaptation and Few-Shot Learning
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 6 February 2026