activity
20172022
most citedEDS-MEMBED: Multi-sense embeddings based on enhanced distributional semantic structures via a graph walk over word senses

13 citations · 17 across the 6 of their papers we have counts for

collaborators

9 papers

cs.CL2022

Adaptor: Objective-Centric Adaptation Framework for Language Models

Michal Štefánik, Vít Novotný, Nikola Groverová +1

Progress in natural language processing research is catalyzed by the possibilities given by the widespread software frameworks. This paper introduces Adaptor library that transpose…

cs.IR2021

Towards Math-Aware Automated Classification and Similarity Search of Scientific Publications: Methods of Mathematical Content Representations

Michal Růžička, Petr Sojka

In this paper, we investigate mathematical content representations suitable for the automated classification of and the similarity search in STEM documents using standard machine l…

cs.CL20214 cited

Regressive Ensemble for Machine Translation Quality Evaluation

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. We evaluate the ensemble using a corre…

cs.DL2021

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

Dávid Lupták, Vít Novotný, Michal Štefánik +1

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 a…

cs.CL202113 cited

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

Eniafe Festus Ayetiran, Petr Sojka, Vít Novotný

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 embe…

cs.CL2021

One Size Does Not Fit All: Finding the Optimal Subword Sizes for FastText Models across Languages

Vít Novotný, Eniafe Festus Ayetiran, Dalibor Bačovský +3

Unsupervised representation learning of words from large multilingual corpora is useful for downstream tasks such as word sense disambiguation, semantic text similarity, and inform…