Sept. 27, 2022, 1:14 a.m. | Nicolas Webersinke, Mathias Kraus, Julia Anna Bingler, Markus Leippold

cs.CL updates on arXiv.org arxiv.org

Over the recent years, large pretrained language models (LM) have
revolutionized the field of natural language processing (NLP). However, while
pretraining on general language has been shown to work very well for common
language, it has been observed that niche language poses problems. In
particular, climate-related texts include specific language that common LMs can
not represent accurately. We argue that this shortcoming of today's LMs limits
the applicability of modern NLP to the broad field of text processing of
climate-related …

arxiv climate language language model pretrained language model text

AI Research Scientist

@ Vara | Berlin, Germany and Remote

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Lead Data Scientist, Commercial Analytics

@ Checkout.com | London, United Kingdom

Data Engineer I

@ Love's Travel Stops | Oklahoma City, OK, US, 73120