György Szarvas

According to our database, György Szarvas authored at least 38 papers between 2004 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Few Shot Rationale Generation using Self-Training with Dual Teachers.

Aditya Srikanth Veerubhotla, Lahari Poddar, Jun Yin, György Szarvas, Sharanya Eswaran

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022

Calibrating Imbalanced Classifiers with Focal Loss: An Empirical Study.

Cheng Wang, Jorge Balazs, György Szarvas, Patrick Ernst, Lahari Poddar, Pavel Danchenko

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: EMNLP 2022 - Industry Track, Abu Dhabi, UAE, December 7, 2022

Deploying a Retrieval based Response Model for Task Oriented Dialogues.

Lahari Poddar, György Szarvas, Cheng Wang, Jorge Balazs, Pavel Danchenko, Patrick Ernst

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: EMNLP 2022 - Industry Track, Abu Dhabi, UAE, December 7, 2022

Transformer Uncertainty Estimation with Hierarchical Stochastic Attention.

Jiahuan Pei, Cheng Wang, György Szarvas

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2020

The Multilingual Amazon Reviews Corpus.

Phillip Keung, Yichao Lu, György Szarvas, Noah A. Smith

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

2019

A Probabilistic Framework for Learning Domain Specific Hierarchical Word Embeddings.

Lahari Poddar, György Szarvas, Lea Frermann

CoRR, 2019

2017

Inducing Semantic Micro-Clusters from Deep Multi-View Representations of Novels.

Lea Frermann, György Szarvas

Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017

2013

Tune and mix: learning to rank using ensembles of calibrated multi-class classifiers.

Róbert Busa-Fekete, Balázs Kégl, Tamás Éltetö, György Szarvas

Mach. Learn., 2013

Supervised All-Words Lexical Substitution using Delexicalized Features.

György Szarvas, Chris Biemann, Iryna Gurevych

Proceedings of the Human Language Technologies: Conference of the North American Chapter of the Association of Computational Linguistics, 2013

Uncertainty Detection for Natural Language Watermarking.

György Szarvas, Iryna Gurevych

Proceedings of the Sixth International Joint Conference on Natural Language Processing, 2013

Learning to Rank Lexical Substitutions.

György Szarvas, Róbert Busa-Fekete, Eyke Hüllermeier

Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, 2013

2012

Cross-Genre and Cross-Domain Detection of Semantic Uncertainty.

György Szarvas, Veronika Vincze, Richárd Farkas, György Móra, Iryna Gurevych

Comput. Linguistics, 2012

2011

Ranking by calibrated AdaBoost.

Róbert Busa-Fekete, Balázs Kégl, Tamás Éltetö, György Szarvas

Proceedings of the Yahoo! Learning to Rank Challenge, 2011

Linguistic scope-based and biological event-based speculation and negation annotations in the BioScope and Genia Event corpora.

Veronika Vincze, György Szarvas, György Móra, Tomoko Ohta, Richárd Farkas

J. Biomed. Semant., 2011

A Robust Ranking Methodology Based on Diverse Calibration of AdaBoost.

Róbert Busa-Fekete, Balázs Kégl, Tamás Éltetö, György Szarvas

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

Combining Query Translation Techniques to Improve Cross-Language Information Retrieval.

Benjamin Herbert, György Szarvas, Iryna Gurevych

Proceedings of the Advances in Information Retrieval, 2011

Combining Heterogeneous Knowledge Resources for Improved Distributional Semantic Models.

György Szarvas, Torsten Zesch, Iryna Gurevych

Proceedings of the Computational Linguistics and Intelligent Text Processing, 2011

2010

Linguistic scope-based and biological event-based speculation and negation annotations in the Genia Event and BioScope corpora.

Veronika Vincze, György Szarvas, György Móra, Tomoko Ohta, Richárd Farkas

Proceedings of the Fourth International Symposium for Semantic Mining in Biomedicine, 2010

TUD: Semantic Relatedness for Relation Classification.

György Szarvas, Iryna Gurevych

Proceedings of the 5th International Workshop on Semantic Evaluation, 2010

Combining Language Sources and Robust Semantic Relatedness for Attribute-Based Knowledge Transfer.

Marcus Rohrbach, Michael Stark, György Szarvas, Bernt Schiele

Proceedings of the Trends and Topics in Computer Vision, 2010

What helps where - and why? Semantic relatedness for knowledge transfer.

Marcus Rohrbach, Michael Stark, György Szarvas, Iryna Gurevych, Bernt Schiele

Proceedings of the Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition, 2010

The CoNLL-2010 Shared Task: Learning to Detect Hedges and their Scope in Natural Language Text.

Richárd Farkas, Veronika Vincze, György Móra, János Csirik, György Szarvas

Proceedings of the Fourteenth Conference on Computational Natural Language Learning: Shared Task, 2010

2009

Research Paper: Semi-automated Construction of Decision Rules to Predict Morbidities from Clinical Texts.

Richárd Farkas, György Szarvas, István Hegedüs, Attila Almási, Veronika Vincze, Róbert Ormándi, Róbert Busa-Fekete

J. Am. Medical Informatics Assoc., 2009

Prior Art Search using International Patent Classification Codes and All-Claims-Queries.

György Szarvas, Benjamin Herbert, Iryna Gurevych

Proceedings of the Working Notes for CLEF 2009 Workshop co-located with the 13th European Conference on Digital Libraries (ECDL 2009) , Corfù, Greece, September 30, 2009

Exploring ways beyond the simple supervised learning approach for biological event extraction.

György Móra, Richárd Farkas, György Szarvas, Zsolt Molnár

Proceedings of the BioNLP 2009 Workshop Companion Volume for Shared Task, BioNLP@HLT-NAACL 2009, 2009

2008

The BioScope corpus: biomedical texts annotated for uncertainty, negation and their scopes.

Veronika Vincze, György Szarvas, Richárd Farkas, György Móra, János Csirik

BMC Bioinform., 2008

Automatic construction of rule-based ICD-9-CM coding systems.

Richárd Farkas, György Szarvas

BMC Bioinform., 2008

Web-Based Lemmatisation of Named Entities.

Richárd Farkas, Veronika Vincze, István Nagy T., Róbert Ormándi, György Szarvas, Attila Almási

Proceedings of the Text, Speech and Dialogue, 11th International Conference, 2008

Hungarian Word-Sense Disambiguated Corpus.

Veronika Vincze, György Szarvas, Attila Almási, Dóra Szauter, Róbert Ormándi, Richárd Farkas, Csaba Hatvani, János Csirik

Proceedings of the International Conference on Language Resources and Evaluation, 2008

The BioScope corpus: annotation for negation, uncertainty and their scope in biomedical texts.

György Szarvas, Veronika Vincze, Richárd Farkas, János Csirik

Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing, 2008

Hedge Classification in Biomedical Texts with a Weakly Supervised Selection of Keywords.

György Szarvas

Proceedings of the ACL 2008, 2008

2007

Research Paper: State-of-the-art Anonymization of Medical Records Using an Iterative Machine Learning Framework.

György Szarvas, Richárd Farkas, Róbert Busa-Fekete

J. Am. Medical Informatics Assoc., 2007

GYDER: Maxent Metonymy Resolution.

Richárd Farkas, Eszter Simon, György Szarvas, Dániel Varga

Proceedings of the 4th International Workshop on Semantic Evaluations, 2007

Improving a State-of-the-Art Named Entity Recognition System Using the World Wide Web.

Richárd Farkas, György Szarvas, Róbert Ormándi

Proceedings of the Advances in Data Mining. Theoretical Aspects and Applications, 2007

2006

Named Entity Recognition for Hungarian Using Various Machine Learning Algorithms.

Richárd Farkas, György Szarvas, András Kocsor

Acta Cybern., 2006

A highly accurate Named Entity corpus for Hungarian.

György Szarvas, Richárd Farkas, László Felföldi, András Kocsor, János Csirik

Proceedings of the Fifth International Conference on Language Resources and Evaluation, 2006

A Multilingual Named Entity Recognition System Using Boosting and C4.5 Decision Tree Learning Algorithms.

György Szarvas, Richárd Farkas, András Kocsor

Proceedings of the Discovery Science, 9th International Conference, 2006

2004

Intelligent Forecast with Dimension Reduction.

István Juhos, György Szarvas

Proceedings of the Applied Soft Computing Technologies: The Challenge of Complexity, Proceedings of the 9th Online World Conference on Soft Computing in Industrial Applications (WSC9), September 20th, 2004