Zobrazeno 1 - 10
of 73
pro vyhledávání: '"Novotny, Vit"'
Although pre-trained named entity recognition (NER) models are highly accurate on modern corpora, they underperform on historical texts due to differences in language OCR errors. In this work, we develop a new NER corpus of 3.6M sentences from late m
Externí odkaz:
http://arxiv.org/abs/2305.16718
Progress in natural language processing research is catalyzed by the possibilities given by the widespread software frameworks. This paper introduces Adaptor library that transposes the traditional model-centric approach composed of pre-training + fi
Externí odkaz:
http://arxiv.org/abs/2203.03989
Chromatography-free synthesis of 2A,2B-disulfonated β-cyclodextrin for regiospecific di-substitution
Publikováno v:
In Carbohydrate Polymers 15 January 2025 348 Part B
This work introduces a simple regressive ensemble for evaluating machine translation quality based on a set of novel and established metrics. We evaluate the ensemble using a correlation to expert-based MQM scores of the WMT 2021 Metrics workshop. In
Externí odkaz:
http://arxiv.org/abs/2109.07242
Math informational retrieval (MIR) search engines are absent in the wide-spread production use, even though documents in the STEM fields contain many mathematical formulae, which are sometimes more important than text for understanding. We have devel
Externí odkaz:
http://arxiv.org/abs/2106.00411
Publikováno v:
J. Univers. Comput. Sci. 28:2 (2022) 181-201
In 2018, Mikolov et al. introduced the positional language model, which has characteristics of attention-based neural machine translation models and which achieved state-of-the-art performance on the intrinsic word analogy task. However, the position
Externí odkaz:
http://arxiv.org/abs/2104.09691
Publikováno v:
Knowledge-Based Systems. 219 (2021) 106902
Several language applications often require word semantics as a core part of their processing pipeline, either as precise meaning inference or semantic similarity. Multi-sense embeddings (M-SE) can be exploited for this important requirement. M-SE se
Externí odkaz:
http://arxiv.org/abs/2103.00232
Autor:
Novotný, Vít, Ayetiran, Eniafe Festus, Bačovský, Dalibor, Lupták, Dávid, Štefánik, Michal, Sojka, Petr
Publikováno v:
RANLP (2021) 1072-1078
Unsupervised representation learning of words from large multilingual corpora is useful for downstream tasks such as word sense disambiguation, semantic text similarity, and information retrieval. The representation precision of log-bilinear fastText
Externí odkaz:
http://arxiv.org/abs/2102.02585
Since the seminal work of Mikolov et al., word embeddings have become the preferred word representations for many natural language processing tasks. Document similarity measures extracted from word embeddings, such as the soft cosine measure (SCM) an
Externí odkaz:
http://arxiv.org/abs/2003.05019
Autor:
Novotný, Vít
The standard bag-of-words vector space model (VSM) is efficient, and ubiquitous in information retrieval, but it underestimates the similarity of documents with the same meaning, but different terminology. To overcome this limitation, Sidorov et al.
Externí odkaz:
http://arxiv.org/abs/1808.09407