4 citations · 5 across the 4 of their papers we have counts for
3 papers · 1 filter
Zero and Few-shot Learning for Author Profiling
Mara Chinea-Rios, Thomas Müller, Gretel Liz De la Peña Sarracén +2
Author profiling classifies author characteristics by analyzing how language is shared among people. In this work, we study that task from a low-resource viewpoint: using little or…
Active Few-Shot Learning with FASL
Thomas Müller, Guillermo Pérez-Torró, Angelo Basile +1
Recent advances in natural language processing (NLP) have led to strong text classification models for many tasks. However, still often thousands of examples are needed to train mo…
Few-Shot Learning with Siamese Networks and Label Tuning
Thomas Müller, Guillermo Pérez-Torró, Marc Franco-Salvador
We study the problem of building text classifiers with little or no training data, commonly known as zero and few-shot text classification. In recent years, an approach based on ne…