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Elongation of Very Long-Chain Fatty Acids (ELOVL) in Atopic Dermatitis and the Cutaneous Adverse Effect AGEP of Drugs
Get PDFImage-Based 3D Reconstruction in Laparoscopy : A Review Focusing on the Quantitative Evaluation by Applying the Reconstruction Error
Get PDFLinguistic-Aware WordPiece Tokenization : Semantic Enrichment and OOV Mitigation
No full textThe LinPair approach introduces an approach to tokenization, tackling challenges in processing textual data for machine learning applications. This method refines the Word-Piece Tokenization technique by incorporating linguistic insights into token-tag pairs, thereby enriching Large Language Models (LLMs) with syntactic information. LinPair Tokenization is articulated through two distinct strategies: CompleteLinPair Tokenization, which is tailored for smaller datasets and enriches each token with part-of-speech (POS) information, and SmartLinPair Tokenization, designed to mitigate the impact of out-of-vocabulary (OOV) occurrences. The experimental analysis indicates that SmartLinPair Tokenization improves text classification tasks with BERT, showing an increase in F1-Score of up to 13.9% compared to a WordPiece baseline. The CompleteLinPair Tokenization method results in a decrease in classification performance. It is important to note that these findings are experiment specific and may not be generalizable to other contexts
Combinatorial solid phase peptide synthesis of peptides on glass slides and thermographic investigation on CO2-binding affinity
No full textMeasures to optimize the efficiency, weight and noise emissions of a gearbox for electric light commercial vehicles
No full textVon forschendem Lernen zu lehrendem Forschen? Das geisteswissenschaftliche Konferenzseminar als Brücke zwischen Forschung und Lehre
No full textInfluence of Additives on Grinding Performance of Digital Light Processing-Printed Phenol Bond Grinding Wheels
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