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Found 3 papers, 2 papers with code
Full-Text Argumentation Mining on Scientific Publications
In this work, we introduce a sequential pipeline model combining ADUR and ARE for full-text SAM, and provide a first analysis of the performance of pretrained language models (PLMs) on both subtasks.
A Comparative Study of Pre-trained Encoders for Low-Resource Named Entity Recognition
Pre-trained language models (PLM) are effective components of few-shot named entity recognition (NER) approaches when augmented with continued pre-training on task-specific out-of-domain data or fine-tuning on in-domain data.
Contrastive Learning
Low Resource Named Entity Recognition
+4
An Empirical Comparison of Question Classification Methods for Question Answering Systems
This work makes an extensible review of the most recent methods for Question Classification, taking into consideration their applicability in low-resourced languages.
