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Parameter-Efficient Fine-Tuning: Is There An Optimal Subset of Parameters to Tune?, and . EACL (Findings), page 1743-1759. Association for Computational Linguistics, (2024)Medical Coding with Biomedical Transformer Ensembles and Zero/Few-shot Learning., , , , , and . NAACL-HLT (Industry Papers), page 176-187. Association for Computational Linguistics, (2022)HunFlair: An Easy-to-Use Tool for State-of-the-Art Biomedical Named Entity Recognition., , , , , and . CoRR, (2020)FLERT: Document-Level Features for Named Entity Recognition, and . (2020)cite arxiv:2011.06993.FLAIR: An Easy-to-Use Framework for State-of-the-Art NLP., , , , , and . NAACL-HLT (Demonstrations), page 54-59. Association for Computational Linguistics, (2019)Pooled Contextualized Embeddings for Named Entity Recognition., , and . NAACL-HLT (1), page 724-728. Association for Computational Linguistics, (2019)OpinionGPT: Modelling Explicit Biases in Instruction-Tuned LLMs., , and . CoRR, (2023)HunFlair: an easy-to-use tool for state-of-the-art biomedical named entity recognition., , , , , and . Bioinform., 37 (17): 2792-2794 (2021)CleanCoNLL: A Nearly Noise-Free Named Entity Recognition Dataset., and . EMNLP, page 8628-8645. Association for Computational Linguistics, (2023)Fabricator: An Open Source Toolkit for Generating Labeled Training Data with Teacher LLMs., , , , and . EMNLP (Demos), page 1-11. Association for Computational Linguistics, (2023)