657 citations
- Panjab UniversityIN239 papers
- University of SplitHR239 papers
- Sejong UniversityKR236 papers
- Yonsei UniversityKR236 papers
- Helsinki Institute of PhysicsFI234 papers
- Istituto Nazionale di Fisica Nucleare, Sezione di BolognaIT234 papers
- Istituto Nazionale di Fisica Nucleare, Sezione di TorinoIT234 papers
- A. Alikhanyan National LaboratoryAM233 papers
- European Organization for Nuclear ResearchCH230 papers
- Istituto Nazionale di Fisica Nucleare, Sezione di BariIT230 papers
- Istituto Nazionale di Fisica Nucleare, Sezione di CataniaIT229 papers
- Istituto Nazionale di Fisica Nucleare, Sezione di TriesteIT229 papers
7 papers · 1 filter
Optimizing Large Language Models for Turkish: New Methodologies in Corpus Selection and Training
H. Toprak Kesgin, M. Kaan Yuce, Eren Dogan +7
In this study, we develop and assess new corpus selection and training methodologies to improve the effectiveness of Turkish language models. Specifically, we adapted Large Languag…
Scaling BERT Models for Turkish Automatic Punctuation and Capitalization Correction
Abdulkader Saoud, Mahmut Alomeyr, Himmet Toprak Kesgin +1
This paper investigates the effectiveness of BERT based models for automated punctuation and capitalization corrections in Turkish texts across five distinct model sizes. The model…
Data Augmentation with In-Context Learning and Comparative Evaluation in Math Word Problem Solving
Gulsum Yigit, Mehmet Fatih Amasyali
Math Word Problem (MWP) solving presents a challenging task in Natural Language Processing (NLP). This study aims to provide MWP solvers with a more diverse training set, ultimatel…
Investigating Semi-Supervised Learning Algorithms in Text Datasets
Himmet Toprak Kesgin, Mehmet Fatih Amasyali
Using large training datasets enhances the generalization capabilities of neural networks. Semi-supervised learning (SSL) is useful when there are few labeled data and a lot of unl…
Iterative Mask Filling: An Effective Text Augmentation Method Using Masked Language Modeling
Himmet Toprak Kesgin, Mehmet Fatih Amasyali
Data augmentation is an effective technique for improving the performance of machine learning models. However, it has not been explored as extensively in natural language processin…
From text to multimodal: a survey of adversarial example generation in question answering systems
Gulsum Yigit, Mehmet Fatih Amasyali
Integrating adversarial machine learning with Question Answering (QA) systems has emerged as a critical area for understanding the vulnerabilities and robustness of these systems.…