3 papers
cs.CL2025
A Confidence-based Acquisition Model for Self-supervised Active Learning and Label Correction
Carel van Niekerk, Christian Geishauser, Michael Heck +6
Supervised neural approaches are hindered by their dependence on large, meticulously annotated datasets, a requirement that is particularly cumbersome for sequential tasks. The qua…
cs.CL2024
Learning from Noisy Labels via Self-Taught On-the-Fly Meta Loss Rescaling
Michael Heck, Christian Geishauser, Nurul Lubis +6
Correct labels are indispensable for training effective machine learning models. However, creating high-quality labels is expensive, and even professionally labeled data contains e…
cs.CL2024
Infusing Emotions into Task-oriented Dialogue Systems: Understanding, Management, and Generation
Shutong Feng, Hsien-chin Lin, Christian Geishauser +6
Emotions are indispensable in human communication, but are often overlooked in task-oriented dialogue (ToD) modelling, where the task success is the primary focus. While existing w…