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2020 – today
- 2023
[c6]Zsolt Szántó, Balázs Bánáti, Tamás Zombori:
Enhancing Medication Event Classification with Syntax Parsing and Adversarial Learning. AIAI (1) 2023: 114-124- [c5]György Orosz, Gergo Szabó, Péter Berkecz, Zsolt Szántó, Richárd Farkas:
Advancing Hungarian Text Processing with HuSpaCy: Efficient and Accurate NLP Pipelines. TSD 2023: 58-69 - [i3]Péter Berkecz, György Orosz, Zsolt Szántó, Gergo Szabó, Richárd Farkas:
Hybrid lemmatization in HuSpaCy. CoRR abs/2306.07636 (2023) - [i2]György Orosz, Gergo Szabó, Péter Berkecz, Zsolt Szántó, Richárd Farkas:
Advancing Hungarian Text Processing with HuSpaCy: Efficient and Accurate NLP Pipelines. CoRR abs/2308.12635 (2023) - 2022
- [c4]Péter Kardos, Zsolt Szántó, Richárd Farkas:
WomboCombo results for OAEI 2022. OM@ISWC 2022: 216-219 - [i1]György Orosz, Zsolt Szántó, Péter Berkecz, Gergo Szabó, Richárd Farkas:
HuSpaCy: an industrial-strength Hungarian natural language processing toolkit. CoRR abs/2201.01956 (2022)
2010 – 2019
- 2017
- [c3]Veronika Vincze, Katalin Ilona Simkó, Zsolt Szántó, Richárd Farkas
:
Universal Dependencies and Morphology for Hungarian - and on the Price of Universality. EACL (1) 2017: 356-365 - 2014
- [c2]Katalin Ilona Simkó, Veronika Vincze, Zsolt Szántó, Richárd Farkas:
An Empirical Evaluation of Automatic Conversion from Constituency to Dependency in Hungarian. COLING 2014: 1392-1401 - [c1]Zsolt Szántó, Richárd Farkas:
Special Techniques for Constituent Parsing of Morphologically Rich Languages. EACL 2014: 135-144
Coauthor Index
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