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Found 13 papers, 2 papers with code
Toward Multilingual Identification of Online Registers
We consider cross- and multilingual text classification approaches to the identification of online registers (genres), i. e. text varieties with specific situational characteristics.
Multilingual text classification
Multilingual Word Embeddings
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Explaining Classes through Stable Word Attributions
Input saliency methods have recently become a popular tool for explaining predictions of deep learning models in NLP.
Multilingual and Zero-Shot is Closing in on Monolingual Web Register Classification
This article studies register classification of documents from the unrestricted web, such as news articles or opinion blogs, in a multilingual setting, exploring both the benefit of training on multiple languages and the capabilities for zero-shot cross-lingual transfer.
Explaining Classes through Word Attribution
In this work, we propose a method for explaining classes using deep learning models and the Integrated Gradients feature attribution technique by aggregating explanations of individual examples in text classification to general descriptions of the classes.
Beyond the English Web: Zero-Shot Cross-Lingual and Lightweight Monolingual Classification of Registers
We explore cross-lingual transfer of register classification for web documents.
From Web Crawl to Clean Register-Annotated Corpora
However, two critical steps in the development of web corpora remain challenging: the identification of clean text from source HTML and the assignment of genre or register information to the documents.
A Broad-coverage Corpus for Finnish Named Entity Recognition
We present a new manually annotated corpus for broad-coverage named entity recognition for Finnish.
