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pro vyhledávání: '"Pucknat, Lisa"'
We introduce a linguistically enhanced combination of pre-training methods for transformers. The pre-training objectives include POS-tagging, synset prediction based on semantic knowledge graphs, and parent prediction based on dependency parse trees.
Externí odkaz:
http://arxiv.org/abs/2212.07428
We analyze two Natural Language Inference data sets with respect to their linguistic features. The goal is to identify those syntactic and semantic properties that are particularly hard to comprehend for a machine learning model. To this end, we also
Externí odkaz:
http://arxiv.org/abs/2210.10434
Autor:
Deußer, Tobias, Pielka, Maren, Pucknat, Lisa, Jacob, Basil, Dilmaghani, Tim, Nourimand, Mahdis, Kliem, Bernd, Loitz, Rüdiger, Bauckhage, Christian, Sifa, Rafet
Publikováno v:
Proceedings of the Northern Lights Deep Learning Workshop; Vol. 4 (2023): Proceedings of the Northern Lights Deep Learning Workshop 2023
Finding and amending contradictions in a financial report is crucial for the publishing company and its financial auditors. To automate this process, we introduce a novel approach that incorporates informed pre-training into its transformer-based arc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5624a9965ed859bad34b74915dfbc5bc
This paper presents two data augmentation methods for pre-training, to find critical errors in machine translations. This includes an alignment approach used in traditional machine translation and an imitation method, mimicking the structure of the d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e81c6248a1daf49592cdfb327dad31ab