Kokos Kogkalidis

Visitor
Visitor
T313 Dept. Computer Science
Full researcher profile
https://research.aalto.fi/...

Palkinnot

EuroProofNet STSM

Neural Premise Selection for Agda
Granted funding (public project funding) Department of Computer Science Jan 2023

E. W. Beth Dissertation Prize

Award or honor granted for a specific work Department of Computer Science Jan 2024

Tutkimusryhmät

  • Professorship Garg Vikas, Postdoctoral Researcher
  • Professorship Garg Vikas, Visitor (Faculty)

Julkaisut

Algebraic Positional Encodings

Kokos Kogkalidis, Jean-Philippe Bernardy, Vikas Garg 2025 Advances in Neural Information Processing Systems 37 (NeurIPS 2024)

On Tables with Numbers, with Numbers

Konstantinos Kogkalidis, Stergios Chatzikyriakidis 2025 Proceedings of the 1st Workshop on Language Models for Underserved Communities (LM4UC 2025)

Learning Structure-Aware Representations of Dependent Types

Kokos Kogkalidis, Orestis Melkonian, Jean-Philippe Bernardy 2024 Advances in Neural Information Processing Systems 37 (NeurIPS 2024)

OYXOY : A Modern NLP Test Suite for Modern Greek

Konstantinos Kogkalidis, Stergios Chatzikyriakidis, Eirini Chrysovalantou Giannikouri, Christina Klironomou, Christina Koula, Thelka Pasparaki, Efthymia Sakellariou, Vasiliki Katsouli, Dimitris Papadakis, Erofili Psaltaki, Hara Soupiona 2024 EACL 2024 - 18th Conference of the European Chapter of the Association for Computational Linguistics, Findings of EACL 2024

Nominal Class Assignment in Swahili : A Computational Account

Giada Palmieri, Kokos Kogkalidis 2024 Proceedings of the Tenth Italian Conference on Computational Linguistics (CLiC-it 2024), Pisa, Italy, December 4-6, 2024

Geometry-Aware Supertagging with Heterogeneous Dynamic Convolutions

Kokos Kogkalidis, Michael Moortgat 2023 Proceedings of the 2023 CLASP Conference on Learning with Small Data

Improving BERT Pretraining with Syntactic Supervision

Giorgos Tziafas, Kokos Kogkalidis, Gijs Wijnholds, Michael Moortgat 2023 Proceedings of the 2023 CLASP Conference on Learning with Small Data