3 papers
cs.CL2026
Disentangling Curriculum Learning in NLP: Towards a Unifying Taxonomy
Vanessa Toborek, Florian Seiffarth, Sebastian Müller +1
Despite more than a decade of curriculum learning (CL) research in NLP, the field lacks a principled account of which difficulty function or scheduler to use for a given problem. T…
cs.CL2025
Beyond Shallow Heuristics: Leveraging Human Intuition for Curriculum Learning
Vanessa Toborek, Sebastian Müller, Tim Selbach +2
Curriculum learning (CL) aims to improve training by presenting data from "easy" to "hard", yet defining and measuring linguistic difficulty remains an open challenge. We investiga…
cs.LG2025
CFIRE: A General Method for Combining Local Explanations
Sebastian Müller, Vanessa Toborek, Tamás Horváth +1
We propose a novel eXplainable AI algorithm to compute faithful, easy-to-understand, and complete global decision rules from local explanations for tabular data by combining XAI me…