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Collaborating Authors

 Heiman, Alice


The Accuracy, Robustness, and Readability of LLM-Generated Sustainability-Related Word Definitions

arXiv.org Artificial Intelligence

Thus, this can lead to inconsistencies in research and policy-making. A common language with standardized To address this issue, the Interdisciplinary Panel definitions is crucial for effective climate on Climate Change (IPCC) and the United Nations discussions. However, concerns exist (UN) maintain the online glossaries IPCC about LLMs misrepresenting climate Glossary (IPCC, 2019a,b, 2018), and UNTERM terms. We compared 300 official IPCC (UN, 2024a). Although LLMs have access to glossary definitions with those generated these repositories during training, they are not by GPT-4o-mini, Llama3.1 8B, and Mistral constrained to them during inference. Therefore, 7B, analyzing adherence, robustness, LLMs could further diversify and confuse these and readability using SBERT sentence embeddings.


GPT-SW3: An Autoregressive Language Model for the Nordic Languages

arXiv.org Artificial Intelligence

We have faced all of these challenges in our work on developing the first native LLM for the There is a growing interest in building and applying Nordic (or, more accurately, North Germanic) languages. Large Language Models (LLMs) for languages The LLM, which we call GPT-SW3, other than English. This interest has is a continuation of our previous Swedish-only been fuelled partly by the unprecedented popularity model (Ekgren et al., 2022), and is a collection of ChatGPT