1 citations · 1 across the 3 of their papers we have counts for
8 papers
We Need to Talk About Data: The Importance of Data Readiness in Natural Language Processing
Fredrik Olsson, Magnus Sahlgren
In this paper, we identify the state of data as being an important reason for failure in applied Natural Language Processing (NLP) projects. We argue that there is a gap between ac…
The Singleton Fallacy: Why Current Critiques of Language Models Miss the Point
Magnus Sahlgren, Fredrik Carlsson
This paper discusses the current critique against neural network-based Natural Language Understanding (NLU) solutions known as language models. We argue that much of the current de…
Data Readiness for Natural Language Processing
Fredrik Olsson, Magnus Sahlgren
This document concerns data readiness in the context of machine learning and Natural Language Processing. It describes how an organization may proceed to identify, make available,…
Why Not Simply Translate? A First Swedish Evaluation Benchmark for Semantic Similarity
Tim Isbister, Magnus Sahlgren
This paper presents the first Swedish evaluation benchmark for textual semantic similarity. The benchmark is compiled by simply running the English STS-B dataset through the Google…
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…