Search Results for author: Vít Novotný

Found 6 papers, 3 papers with code

Regressive Ensemble for Machine Translation Quality Evaluation

1 code implementation15 Sep 2021 Michal Štefánik, Vít Novotný, Petr Sojka

This work introduces a simple regressive ensemble for evaluating machine translation quality based on a set of novel and established metrics.

Machine Translation

WebMIaS on Docker: Deploying Math-Aware Search in a Single Line of Code

no code implementations1 Jun 2021 Dávid Lupták, Vít Novotný, Michal Štefánik, Petr Sojka

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.

When FastText Pays Attention: Efficient Estimation of Word Representations using Constrained Positional Weighting

1 code implementation19 Apr 2021 Vít Novotný, Michal Štefánik, Eniafe Festus Ayetiran, Petr Sojka

Since the seminal work of Mikolov et al. (2013a) and Bojanowski et al. (2017), word representations of shallow log-bilinear language models have found their way into many NLP applications.

Language Modelling

EDS-MEMBED: Multi-sense embeddings based on enhanced distributional semantic structures via a graph walk over word senses

no code implementations27 Feb 2021 Eniafe Festus Ayetiran, Petr Sojka, Vít Novotný

We report evaluation results on 11 benchmark datasets involving WSD and Word Similarity tasks and show that our method for enhancing distributional semantic structures improves embeddings quality on the baselines.

Semantic Similarity Semantic Textual Similarity +2

Text classification with word embedding regularization and soft similarity measure

1 code implementation10 Mar 2020 Vít Novotný, Eniafe Festus Ayetiran, Michal Štefánik, Petr Sojka

In our work, we investigate the individual and joint effect of the two word embedding regularization techniques on the document processing speed and the task performance of the SCM and the WMD on text classification.

Classification Document Classification +3

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