Gémes Kinga
PhD hallgató vagyok az BME AUT tanszéken. Elsősorban a szemantikai gráfok és a gráf transzformációk mély tanulása érdekel.
Teljes publikációs lista
Legfrissebb publikációk
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.