Kinga Gémes
PhD student at BME AUT. My main interest are semantic graphs and deep learning of graph transformations.
Full list of publications
Recent publications
2022
Á. Kovács,
K. Gémes,
A. Kornai,
G. Recski:
Explainable lexical entailment with semantic graphs.
In Natural Language Engineering.
K. Gémes,
Á. Kovács,
G. Recski:
Offensive Text Detection Across Languages and Datasets Using Rule-based and Hybrid Methods.
In CIKM’22: Advances in Interpretable Machine Learning and Artificial Intelligence Workshop.
Á. Kovács,
K. Gémes,
E. Iklódi,
G. Recski:
POTATO: exPlainable infOrmation exTrAcTion framewOrk.
In CIKM '22: Proceedings of the 31st ACM International Conference on Information & Knowledge Management.
2021
K. Gémes,
Á. Kovács,
M. Reichel,
G. Recski:
Offensive text detection on English Twitter with deep learning models and rule-based systems.
In FIRE 2021: Forum for Information Retrieval Evaluation.
K. Gémes,
G. Recski:
TUW-Inf at GermEval2021: Rule-based and Hybrid Methods for Detecting Toxic, Engaging, and Fact-Claiming Comments.
In Proceedings of the GermEval 2021 Workshop on the Identification of Toxic, Engaging, and Fact-Claiming Comments.
2020
G. Recski,
Á. Kovács,
K. Gémes,
J. Ács,
A. Kornai:
BME-TUW at SR'20: Lexical grammar induction for surface realization.
In Proceedings of the 3rd Workshop on Multilingual Surface Realisation (MSR 2020).
Á. Kovács,
K. Gémes,
G. Recski,
A. Kornai:
BMEAUT at SemEval-2020 Task 2: Lexical entailment with semantic graphs.
In Proceedings of the 14th International Workshop on Semantic Evaluation.
2019
K. Gémes:
Deep learning of graph transformations.
In MSc Thesis.
Á. Kovács,
G. Recski,
K. Gémes:
Machine comprehension using semantic graphs.
In Proceedings of the Automation and Applied Computer Science Workshop 2019 : AACS'19.