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README.md

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 This is a fine-tuned BERT-based language model to classify NLP-related research papers according to concepts included in the [NLP taxonomy](#nlp-taxonomy). 
 It is a multi-label classifier that can predict concepts from all levels of the NLP taxonomy. 
 If the model identifies a lower-level concept, it did learn to predict both the lower-level concept and its hypernyms in the NLP taxonomy.
-The model is fine-tuned on a weakly labeled dataset of 178,521 scientific papers from the ACL Anthology, the arXiv cs.CL domain, and Scopus.
+The model is fine-tuned on a weakly labeled dataset of 178,521 scientific papers from the ACL Anthology, the arXiv cs.CL category, and Scopus.
 Prior to fine-tuning, the model is initialized with weights from [allenai/specter2_base](https://huggingface.co/allenai/specter2_base).
 
 📄 Paper: [Exploring the Landscape of Natural Language Processing Research (RANLP 2023)](https://aclanthology.org/2023.ranlp-1.111)