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Found 8 papers, 7 papers with code
A Multilingual Approach to Identify and Classify Exceptional Measures against COVID-19
The COVID-19 pandemic has witnessed the implementations of exceptional measures by governments across the world to counteract its impact.
Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Cross-lingual transfer learning with large multilingual pre-trained models can be an effective approach for low-resource languages with no labeled training data.
DUMB: A Benchmark for Smart Evaluation of Dutch Models
The benchmark includes a diverse set of datasets for low-, medium- and high-resource tasks.
Adapting Monolingual Models: Data can be Scarce when Language Similarity is High
For many (minority) languages, the resources needed to train large models are not available.
As Good as New. How to Successfully Recycle English GPT-2 to Make Models for Other Languages
Specifically, we describe the adaptation of English GPT-2 to Italian and Dutch by retraining lexical embeddings without tuning the Transformer layers.
Neural Representations for Modeling Variation in Speech
We show that speech representations extracted from a specific type of neural model (i. e. Transformers) lead to a better match with human perception than two earlier approaches on the basis of phonetic transcriptions and MFCC-based acoustic features.
What's so special about BERT's layers? A closer look at the NLP pipeline in monolingual and multilingual models
Peeking into the inner workings of BERT has shown that its layers resemble the classical NLP pipeline, with progressively more complex tasks being concentrated in later layers.
BERTje: A Dutch BERT Model
The transformer-based pre-trained language model BERT has helped to improve state-of-the-art performance on many natural language processing (NLP) tasks.
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