3 papers
cs.LG2026
Teaching and Learning under Deductive Errors
Jan Arne Telle, Brigt HÃ¥vardstun, Jose Hernandez-Orallo
Most models of machine teaching and learning assume the learner makes no errors in its internal deductive inference. However, humans and large language models in few-shot learning…
cs.LG2025
Evaluating Simplification Algorithms for Interpretability of Time Series Classification
Brigt Håvardstun, Felix Marti-Perez, Cèsar Ferri +1
In this work, we introduce metrics to evaluate the use of simplified time series in the context of interpretability of a TSC -- a Time Series Classifier. Such simplifications are i…
cs.CV2025
Relative Drawing Identification Complexity is Invariant to Modality in Vision-Language Models
Diogo Freitas, Brigt Håvardstun, Cèsar Ferri +3
Large language models have become multimodal, and many of them are said to integrate their modalities using common representations. If this were true, a drawing of a car as an imag…