Výpis publikací

NOVOTNÝ, Vít. Co nám jazykové modely říkají o manželství? Běstvina, 2023.

STARÝ NOVOTNÝ, Vít. Markdown 3: What's new, what's next? In TUG 2023. 2023.

STARÝ NOVOTNÝ, Vít. Nápadovník jmen pro tvůrčí psaní v LuaTeXu. Zpravodaj CSTUG. Brno: CSTUG, 2023, roč. 33, 1-2, s. 3-38. ISSN 1211-6661. Dostupné z: https://dx.doi.org/10.5300/2023-1-2/3.

HORÁK, Aleš, Adam RAMBOUSEK, Pavel RYCHLÝ, Vít NOVOTNÝ a Tereza VRABCOVÁ. Nástroj na extrakci pojmenovaných entit a vztahů ze skenovaných textů. 2023.

NOVOTNÝ, Vít, Kristýna LUGER, Michal ŠTEFÁNIK, Tereza VRABCOVÁ a Aleš HORÁK. People and Places of Historical Europe: Bootstrapping Annotation Pipeline and a New Corpus of Named Entities in Late Medieval Texts. Online. In Anna Rogers, Jordan Boyd-Graber, Naoaki Okazaki. Findings of the Association for Computational Linguistics: ACL 2023. Toronto, Canada: Association for Computational Linguistics, 2023, s. 14104-14113. ISBN 978-1-959429-62-3.

HORÁK, Aleš, Adam RAMBOUSEK, Pavel RYCHLÝ, Vít NOVOTNÝ a Tereza VRABCOVÁ. Systém portálu AHISTO. 2023.

ŠTEFÁNIK, Michal, Vít NOVOTNÝ, Nikola GROVEROVÁ a Petr SOJKA. AdaptOr: Objective-Centric Adaptation Framework for Language Models. Online. In Valerio Basile, Zornitsa Kozareva, Sanja Stajner. Proceedings of the 60th Conference of Association of Computational Linguistics, ACL 2022. Dublin, Irsko: Association for Computational Linguistics, ACL, 2022, s. 261-269. ISBN 978-1-955917-24-7. Dostupné z: https://dx.doi.org/10.18653/v1/2022.acl-demo.26.

NOVOTNÝ, Vít a Michal ŠTEFÁNIK. Combining Sparse and Dense Information Retrieval: Soft Vector Space Model and MathBERTa at ARQMath-3 Task 1 (Answer Retrieval). Online. In Guglielmo Faggioli, Nicola Ferro, Allan Hanbury, Martin Potthast. Proceedings of the Working Notes of CLEF 2022 - Conference and Labs of the Evaluation Forum. Bologna: CEUR-WS, 2022, s. 104-118. ISSN 1613-0073.

NOVOTNÝ, Vít, Dominik REHÁK, Michal HOFTICH a Tereza VRABCOVÁ. Markdown 2.15.0: What's new? TUGboat. Portland, OR 97208-2311, U.S.A: TUG, 2022, roč. 43, č. 1, 6 s. ISSN 0896-3207. Dostupné z: https://dx.doi.org/10.47397/tb/43-1/tb133novotny-markdown.

MANSOURI, Behrooz, Vít NOVOTNÝ, Anurag AGARWAL, Douglas W. OARD a Richard ZANIBBI. Overview of ARQMath-3 (2022): Third CLEF Lab on Answer Retrieval for Questions on Math (Working Notes Version). Online. In Guglielmo Faggioli, Nicola Ferro, Allan Hanbury, Martin Potthast. Proceedings of the Working Notes of CLEF 2022 - Conference and Labs of the Evaluation Forum. Bologna: CEUR-WS, 2022, s. 1-27. ISSN 1613-0073.

NOVOTNÝ, Vít. Vysokoúrovňové jazyky pro TeX. Zpravodaj CSTUG. Brno: CSTUG, 2022, roč. 32, 1-4, s. 25-48. ISSN 1211-6661. Dostupné z: https://dx.doi.org/10.5300/2022-1-4/35.

NOVOTNÝ, Vít, Michal ŠTEFÁNIK, Eniafe Festus AYETIRAN, Petr SOJKA a Radim ŘEHŮŘEK. When FastText Pays Attention: Efficient Estimation of Word Representations using Constrained Positional Weighting. Journal of Universal Computer Science. New York, USA: J.UCS Consortium, 2022, roč. 28, č. 2, s. 181-201. ISSN 0948-695X. Dostupné z: https://dx.doi.org/10.3897/jucs.69619.

NOVOTNÝ, Vít a Aleš HORÁK. When Tesseract Meets PERO : Open-Source Optical Character Recognition of Medieval Texts. In Aleš Horák, Pavel Rychlý, Adam Rambousek. Proceedings of the Sixteenth Workshop on Recent Advances in Slavonic Natural Languages Processing, RASLAN 2022. Brno: Tribun EU, 2022, s. 157-161. ISBN 978-80-263-1752-4.

BANKOVIČ, Mikuláš, Vít NOVOTNÝ a Petr SOJKA. Application of Super-Resolution Models in Optical Character Recognition of Czech Medieval Texts. In Horák, Rychlý, Rambousek. Recent Advances in Slavonic Natural Language Processing (RASLAN 2021). Brno: Tribun EU, 2021, s. 11-18. ISBN 978-80-263-1670-1.

LÍŠKA, Martin, Dávid LUPTÁK, Vít STARÝ NOVOTNÝ, Michal RŮŽIČKA, Boris SHMINKE, Petr SOJKA, Michal ŠTEFÁNIK a Makarius WENZEL. CICM'21 Systems Entries. Online. In 978-3-030-81097-9. INTELLIGENT COMPUTER MATHEMATICS (CICM 2021). CHAM: SPRINGER INTERNATIONAL PUBLISHING AG, 2021, s. 245-248. ISBN 978-3-030-81096-2. Dostupné z: https://dx.doi.org/10.1007/978-3-030-81097-9_20.

AYETIRAN, Eniafe Festus, Petr SOJKA a Vít NOVOTNÝ. EDS-MEMBED: Multi-sense embeddings based on enhanced distributional semantic structures via a graph walk over word senses. Knowledge-Based Systems. Elsevier, 2021, roč. 2021, č. 219, s. 106902-106915. ISSN 0950-7051. Dostupné z: https://dx.doi.org/10.1016/j.knosys.2021.106902.

NOVOTNÝ, Vít, Michal ŠTEFÁNIK, Dávid LUPTÁK, Martin GELETKA, Petr ZELINA a Petr SOJKA. Ensembling Ten Math Information Retrieval Systems: MIRMU and MSM at ARQMath 2021. Online. In Guglielmo Faggioli. CEUR Workshop Proceedings. Bucharest, Romania: M. Jeusfeld c/o Redaktion Sun SITE, Informatik V, RWTH Aachen, 2021, s. 82-106. ISSN 1613-0073.

NOVOTNÝ, Vít. Interpretable Document Representations for Fast and Accurate Retrieval of Mathematical Information. Online. In SIGIR '21: Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, 2021, s. 2705-2705. ISBN 978-1-4503-3621-5. Dostupné z: https://dx.doi.org/10.1145/3404835.3463269.

NOVOTNÝ, Vít. Markdown 2.10.0: LaTeX themes & snippets, two flavors of comments, and LuaMetaTeX. TUGboat. Portland, OR 97208-2311, U.S.A: TUG, 2021, roč. 42, č. 2, 8 s. ISSN 0896-3207. Dostupné z: https://dx.doi.org/10.47397/tb/42-2/tb131novotny-markdown.

NOVOTNÝ, Vít. Markdown 2.10.0: LaTeXová témata a snippety. Zpravodaj CSTUG. Brno: CSTUG, 2021, roč. 31, 1-4, s. 76-82. ISSN 1211-6661. Dostupné z: https://dx.doi.org/10.5300/2021-1-4/76.

NOVOTNÝ, Vít, Eniafe Festus AYETIRAN, Dalibor BAČOVSKÝ, Dávid LUPTÁK, Michal ŠTEFÁNIK a Petr SOJKA. One Size Does Not Fit All: Finding the Optimal Subword Sizes for FastText Models across Languages. In Mitkov, Ruslan and Angelova, Galia. Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021). Varna, Bulgaria: INCOMA Ltd., 2021, s. 1068-1074. ISBN 978-954-452-072-4. Dostupné z: https://dx.doi.org/10.26615/978-954-452-072-4_120.

NOVOTNÝ, Vít. Overleaf: Kolaborativní webový editor LaTeXu. Zpravodaj CSTUG. Brno: CSTUG, 2021, roč. 31, 1-4, s. 3-8. ISSN 1211-6661. Dostupné z: https://dx.doi.org/10.5300/2021-1-4/3.

ŠTEFÁNIK, Michal, Vít NOVOTNÝ a Petr SOJKA. Regressive Ensemble for Machine Translation Quality Evaluation. Online. In Loïc Barrault et al. Proceedings of EMNLP 2021 Sixth Conference on Machine Translation (WMT 21). Online and Punta Cana, Dominican Republi: ACL, 2021, s. 1041-1048. ISBN 978-1-954085-94-7.

LUPTÁK, Dávid, Vít NOVOTNÝ, Michal ŠTEFÁNIK a Petr SOJKA. WebMIaS on Docker: Deploying Math-Aware Search in a Single Line of Code. In Fairouz Kamareddine and Claudio Sacerdotti-Coen. Intelligent Computer Mathematics: 14th International Conference, CICM 2021, Timisoara, Romania, July 26–31, 2021, Proceedings. LNAI 12833. Timisoara, Romania: Springer, 2021, s. 159-164. ISBN 978-3-030-81096-2. Dostupné z: https://dx.doi.org/10.1007/978-3-030-81097-9_13.

NOVOTNÝ, Vít, Kristýna SEIDLOVÁ, Tereza VRABCOVÁ a Aleš HORÁK. When Tesseract Brings Friends: Layout Analysis, Language Identification, and Super-Resolution in the Optical Character Recognition of Medieval Texts. In Horák, Rychlý, Rambousek. Recent Advances in Slavonic Natural Language Processing (RASLAN 2021). Brno: Tribun EU, 2021, s. 29-39. ISBN 978-80-263-1670-1.

NOVOTNÝ, Vít a Marie STARÁ. Cthulhu Hails from Wales: N-gram Frequency Analysis of R'lyehian. In Aleš Horák, Pavel Rychlý, Adam Rambousek. Proceedings of the Fourteenth Workshop on Recent Advances in Slavonic Natural Language Processing, RASLAN 2020. Brno: Tribun EU, 2020, s. 87-92. ISBN 978-80-263-1600-8.

NOVOTNÝ, Vít. Making Markdown into a microwave meal. TUGboat. Portland, OR 97208-2311, U.S.A: TUG, 2020, roč. 41, č. 3, 3 s. ISSN 0896-3207. Dostupné z: https://dx.doi.org/10.47397/tb/41-3/tb129novotny-frozen.

NOVOTNÝ, Vít. Markdown 2.8.1: Směle k trůnu odlehčeného značkování v TeXu. Zpravodaj CSTUG. Brno: CSTUG, 2020, roč. 30, 1-2, s. 48-56. ISSN 1211-6661. Dostupné z: https://dx.doi.org/10.5300/2020-1-2/48.

NOVOTNÝ, Vít. The Art of Reproducible Machine Learning: A Survey of Methodology in Word Vector Experiments. In Aleš Horák, Pavel Rychlý, Adam Rambousek. Proceedings of the Fourteenth Workshop on Recent Advances in Slavonic Natural Language Processing, RASLAN 2020. Brno: Tribun EU, 2020, s. 55-64. ISBN 978-80-263-1600-8.

NOVOTNÝ, Vít, Petr SOJKA, Michal ŠTEFÁNIK a Dávid LUPTÁK. Three is Better than One: Ensembling Math Information Retrieval Systems. CEUR Workshop Proceedings. Thessaloniki, Greece: M. Jeusfeld c/o Redaktion Sun SITE, Informatik V, RWTH Aachen., 2020, roč. 2020, č. 2696, s. 93-122. ISSN 1613-0073.

NOVOTNÝ, Vít, Michal ŠTEFÁNIK, Dávid LUPTÁK a Petr SOJKA. Towards Useful Word Embeddings: Evaluation on Information Retrieval, Text Classification, and Language Modeling. In Aleš Horák and Pavel Rychlý and Adam Rambousek. Proceedings of the Fourteenth Workshop on Recent Advances in Slavonic Natural Language Processing, RASLAN 2020. Brno: Tribun EU, 2020, s. 37-46. ISBN 978-80-263-1600-8.

NOVOTNÝ, Vít. When Tesseract Does It Alone: Optical Character Recognition of Medieval Texts. In Aleš Horák, Pavel Rychlý, Adam Rambousek. Proceedings of the Fourteenth Workshop on Recent Advances in Slavonic Natural Language Processing, RASLAN 2020. Brno: Tribun EU, 2020, s. 3-12. ISBN 978-80-263-1600-8.

NOVOTNÝ, Vít. Markdown 2.7.0: Towards lightweight markup in TeX. TUGboat. Portland, OR 97208-2311, U.S.A: TUG, 2019, roč. 40, č. 1, s. 25-27. ISSN 0896-3207.

SOJKA, Petr, Vít NOVOTNÝ, Eniafe Festus AYETIRAN, Dávid LUPTÁK a Michal ŠTEFÁNIK. Quo Vadis, Math Information Retrieval. In Aleš Horák and Pavel Rychlý and Adam Rambousek. Proceedings of the Thirteenth Workshop on Recent Advances in Slavonic Natural Language Processing, RASLAN 2019. Brno: Tribun EU, 2019, s. 117-128. ISBN 978-80-263-1517-9.

SOJKA, Petr a Vít NOVOTNÝ. Semantically Coherent Vector Space Representations. 2019.

NOVOTNÝ, Vít. Soft Cosine Measure: Capturing Term Similarity in the Bag of Words VSM. 2019.

ŠTEFÁNIK, Michal a Vít NOVOTNÝ. Video699: Interconnecting Lecture Recordings with Study Materials. 2019.

NOVOTNÝ, Vít. Implementation Notes for the Soft Cosine Measure. Online. In Proceedings of the 27th ACM International Conference on Information and Knowledge Management (CIKM '18). Torino, Italy: Association for Computing Machinery, 2018, s. 1639-1642. ISBN 978-1-4503-6014-2. Dostupné z: https://dx.doi.org/10.1145/3269206.3269317.

SOJKA, Petr, Michal RŮŽIČKA a Vít NOVOTNÝ. MIaS: Math-Aware Retrieval in Digital Mathematical Libraries. Online. In Proceedings of the 27th ACM International Conference on Information and Knowledge Management (CIKM '18). Torino, Italy: Association for Computing Machinery, 2018, s. 1923-1926. ISBN 978-1-4503-6014-2. Dostupné z: https://dx.doi.org/10.1145/3269206.3269233.

NOVOTNÝ, Vít. Příprava Zpravodaje CSTUG. Zpravodaj CSTUG. Brno: CSTUG, 2018, roč. 28, 1-4, s. 1-10. ISSN 1211-6661. Dostupné z: https://dx.doi.org/10.5300/2018-1-4/1.

NOVOTNÝ, Vít. Slide retrieval based on lecture recordings. Brno, 2018, 27 s.

NOVOTNÝ, Vít a Petr SOJKA. Weighting of Passages in Question Answering. In Aleš Horák, Pavel Rychlý, Adam Rambousek. Proceedings of the Twelfth Workshop on Recent Advances in Slavonic Natural Language Processing, RASLAN 2018. Brno: Tribun EU, 2018, s. 31-40. ISBN 978-80-263-1517-9.

RŮŽIČKA, Michal, Vít NOVOTNÝ, Petr SOJKA, Jan POMIKÁLEK a Radim ŘEHŮŘEK. Flexible Similarity Search of Semantic Vectors Using Fulltext Search Engines. Online. In CEUR Workshop Proceedings, Vol. 1923. Vienna, Austria: Neuveden, 2017, s. 1-12. ISSN 1613-0073.

RYGL, Jan, Jan POMIKÁLEK, Radim ŘEHŮŘEK, Michal RŮŽIČKA, Vít NOVOTNÝ a Petr SOJKA. Semantic Vector Encoding and Similarity Search Using Fulltext Search Engines. Online. In Proceedings of the 2nd Workshop on Representation Learning for NLP, RepL4NLP 2017 c/o ACL 2017. Vancouver, Canada: Association for Computational Linguistics, ACL, 2017, s. 81-90. ISBN 978-1-945626-62-3. Dostupné z: https://dx.doi.org/10.18653/v1/W17-2611.

SOJKA, Petr a Vít NOVOTNÝ. TeX in Schools? Just Say Yes: the Use Case of TeX Usage at the Faculty of Informatics, Masaryk University. In XXV Międzynarodowa Konferencja Użytkowników Systemu TeX, Materiały konferencyjne. 2017. ISBN 978-83-939016-4-7.

SOJKA, Petr a Vít NOVOTNÝ. TeX in Schools? Just Say Yes: the Use Case of TeX Usage at the Faculty of Informatics, Masaryk University. TUGboat. Portland, OR 97208-2311, U.S.A: TUG, 2017, roč. 38, č. 2, s. 175-184. ISSN 0896-3207.

SOJKA, Petr a Vít NOVOTNÝ. TeX na školách? Samozřejmě ano! Příklad užití TeXu na Fakultě informatiky Masarykovy univerzity. Zpravodaj CSTUG. Brno: CSTUG, 2017, roč. 27, 3-4, s. 118-137. ISSN 1211-6661. Dostupné z: https://dx.doi.org/10.5300/2017-3-4/118.

NOVOTNÝ, Vít. Using Markdown Inside TeX Documents. In Tomasz Przechlewski, Karl Berry, Jerzy Ludwichowski. XXV Międzynarodowa Konferencja Użytkowników Systemu TeX, Materiały konferencyjne. Portland, OR 97208-2311, U.S.A: Polska Grupa Użytkowników systemu TeX – GUST, 2017, s. 50-53. ISBN 978-83-939016-4-7.

NOVOTNÝ, Vít. Using Markdown Inside TeX Documents. TUGboat. Portland, OR 97208-2311, U.S.A: TUG, 2017, roč. 38, č. 2, s. 214-217. ISSN 0896-3207.

NOVOTNÝ, Vít. Vector Space Representations in Information Retrieval. Brno: Fakulta Informatiky Masarykovy Univerzity, 2017, 56 s.

NOVOTNÝ, Vít. Sazba textu označkovaného v jazyce Markdown uvnitř TeXových dokumentů. Zpravodaj CSTUG. Brno: CSTUG, 2016, roč. 26, 1-4, s. 78-93. ISSN 1211-6661. Dostupné z: https://dx.doi.org/10.5300/2016-1-4/78.

NOVOTNÝ, Vít. The beamer theme for the typesetting of thesis defense presentations at the Masaryk University in Brno. 2015.

NOVOTNÝ, Vít. The fithesis3 class for the typesetting of theses written at the Masaryk University in Brno. 2015.

NOVOTNÝ, Vít. The trends in the usage of TeX in the theses and dissertations defended at the Masaryk University in Brno. Zpravodaj CSTUG. Brno: CSTUG, 2015, roč. 25, 1-2, s. 80-85. ISSN 1211-6661. Dostupné z: https://dx.doi.org/10.5300/2015-1-2/80.