4 citations · 8 across the 2 of their papers we have counts for
5 papers · 1 filter
GPT-SW3: An Autoregressive Language Model for the Nordic Languages
Ariel Ekgren, Amaru Cuba Gyllensten, Felix Stollenwerk +7
This paper details the process of developing the first native large generative language model for the Nordic languages, GPT-SW3. We cover all parts of the development process, from…
The Nordic Pile: A 1.2TB Nordic Dataset for Language Modeling
Joey Öhman, Severine Verlinden, Ariel Ekgren +5
Pre-training Large Language Models (LLMs) require massive amounts of text data, and the performance of the LLMs typically correlates with the scale and quality of the datasets. Thi…
Measuring Issue Ownership using Word Embeddings
Amaru Cuba Gyllensten, Magnus Sahlgren
Sentiment and topic analysis are common methods used for social media monitoring. Essentially, these methods answers questions such as, "what is being talked about, regarding X", a…
R-grams: Unsupervised Learning of Semantic Units in Natural Language
Ariel Ekgren, Amaru Cuba Gyllensten, Magnus Sahlgren
This paper investigates data-driven segmentation using Re-Pair or Byte Pair Encoding-techniques. In contrast to previous work which has primarily been focused on subword units for…
Distributional Term Set Expansion
Amaru Cuba Gyllensten, Magnus Sahlgren
This paper is a short empirical study of the performance of centrality and classification based iterative term set expansion methods for distributional semantic models. Iterative t…