2 citations · 3 across the 4 of their papers we have counts for
4 papers
DPRK-BERT: The Supreme Language Model
Arda Akdemir, Yeojoo Jeon
Deep language models have achieved remarkable success in the NLP domain. The standard way to train a deep language model is to employ unsupervised learning from scratch on a large…
Analyzing the Effect of Multi-task Learning for Biomedical Named Entity Recognition
Arda Akdemir, Tetsuo Shibuya
Developing high-performing systems for detecting biomedical named entities has major implications. State-of-the-art deep-learning based solutions for entity recognition often requi…
Overview of CLEF 2019 Lab ProtestNews: Extracting Protests from News in a Cross-context Setting
Ali Hürriyetoğlu, Erdem Yörük, Deniz Yüret +5
We present an overview of the CLEF-2019 Lab ProtestNews on Extracting Protests from News in the context of generalizable natural language processing. The lab consists of document,…
Hierarchical Multi Task Learning with Subword Contextual Embeddings for Languages with Rich Morphology
Arda Akdemir, Tetsuo Shibuya, Tunga Güngör
Morphological information is important for many sequence labeling tasks in Natural Language Processing (NLP). Yet, existing approaches rely heavily on manual annotations or externa…