Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Tomasz Stanisławek"'
Autor:
Tomasz Stanisławek, Agnieszka K. Kaliska, Dawid Lipiński, Przemyslaw Biecek, Bartosz Topolski, Anna Wróblewska, Filip Graliński, Paulina Rosalska
Publikováno v:
Document Analysis and Recognition – ICDAR 2021 ISBN: 9783030865481
ICDAR (1)
ICDAR (1)
The relevance of the Key Information Extraction (KIE) task is increasingly important in natural language processing problems. But there are still only a few well-defined problems that serve as benchmarks for solutions in this area. To bridge this gap
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e6d6864a0b0aa126012e7ca14974f0c2
https://doi.org/10.1007/978-3-030-86549-8_36
https://doi.org/10.1007/978-3-030-86549-8_36
Autor:
Piotr Halama, Michał Turski, Filip Graliński, Rafał Powalski, Łukasz Garncarek, Bartosz Topolski, Tomasz Stanisławek
Publikováno v:
Document Analysis and Recognition – ICDAR 2021 ISBN: 9783030865481
ICDAR (1)
ICDAR (1)
We introduce a simple new approach to the problem of understanding documents where non-trivial layout influences the local semantics. To this end, we modify the Transformer encoder architecture in a way that allows it to use layout features obtained
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1826fae7669069a22f454d7c3ddcf6ed
https://doi.org/10.1007/978-3-030-86549-8_34
https://doi.org/10.1007/978-3-030-86549-8_34
Autor:
Tomasz Stanisławek, Marek Kozłowski, Jaroslaw Protasiewicz, Agata Kopacz, Sławomir Dadas, Witold Pedrycz, Małgorzata Gałźźewska
Publikováno v:
Knowledge-Based Systems. 106:164-178
In this study, we propose the architecture of a content-based recommender system aimed at the selection of reviewers (experts) to evaluate research proposals or articles. We introduce a comprehensive algorithmic framework supported by various techniq
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::72bd2df1bba42532b192240cb66f02c1
https://doi.org/10.1016/j.knosys.2016.05.041
https://doi.org/10.1016/j.knosys.2016.05.041
Publikováno v:
BlackboxNLP@ACL
This paper presents a simple but general and effective method to debug the output of machine learning (ML) supervised models, including neural networks. The algorithm looks for features that lower the evaluation metric in such a way that it cannot be
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c56fae2f32c586f62b1903ff7203371a
https://doi.org/10.18653/v1/w19-4826
https://doi.org/10.18653/v1/w19-4826
Publikováno v:
FedCSIS (Position Papers)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9a978d896f71c25379a1801553d495a7
https://doi.org/10.15439/2018f373
https://doi.org/10.15439/2018f373
Publikováno v:
SMC
The aim of this paper was to propose a classification system composed of monolingual classifiers and a multilingual decision module, for handling large numbers of multilingual documents. The system was compared with two monolingual classifiers, respe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::67e428bf2a890c347a260b03537535e9
https://doi.org/10.1109/smc.2015.294
https://doi.org/10.1109/smc.2015.294
Publikováno v:
Scopus-Elsevier
CoNLL
Anna Wróblewska
CoNLL
Anna Wróblewska
Recent developments in Named Entity Recognition (NER) have resulted in better and better models. However, is there a glass ceiling? Do we know which types of errors are still hard or even impossible to correct? In this paper, we present a detailed an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3c4c0ed91dcc1fdcd1ad0871faa43031
http://www.scopus.com/inward/record.url?eid=2-s2.0-85084341833&partnerID=MN8TOARS
http://www.scopus.com/inward/record.url?eid=2-s2.0-85084341833&partnerID=MN8TOARS