activity
20202026
most citedTheoretical research on generative diffusion models: an overview

19 citations · 70 across the 20 of their papers we have counts for

collaborators

20 papers

cs.AI2026

Generating Attacks for LLMs with GFlowNets

Berkay Ozcam, Irem Onen, Mehmet Fatih Amasyali +1

The rapid advancement of Large Language Models (LLMs) has facilitated their ubiquitous integration into various domains, leading to widespread adoption. However, this escalating tr…

cs.CV2025★ 12 cited

Robust Change Captioning in Remote Sensing: SECOND-CC Dataset and MModalCC Framework

Ali Can Karaca, M. Enes Ozelbas, Saadettin Berber +3

Remote sensing change captioning (RSICC) aims to describe changes between bitemporal images in natural language. Existing methods often fail under challenges like illumination diff…

cs.CL2024★ 10 cited

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…

cs.AI2024★ 3 cited

Cosmos-LLaVA: Chatting with the Visual Cosmos-LLaVA: Görselle Sohbet Etmek

Ahmed Zeer, Eren Dogan, Yusuf Erdem +7

In this study, a Turkish visual instruction model was developed and various model architectures and dataset combinations were analysed to improve the performance of this model. The…

cs.CL2024

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…

cs.CL2024★ 1 cited

LegalTurk Optimized BERT for Multi-Label Text Classification and NER

Farnaz Zeidi, Mehmet Fatih Amasyali, Çiğdem Erol

The introduction of the Transformer neural network, along with techniques like self-supervised pre-training and transfer learning, has paved the way for advanced models like BERT.…

cs.CL2024★ 1 cited

Introducing cosmosGPT: Monolingual Training for Turkish Language Models

H. Toprak Kesgin, M. Kaan Yuce, Eren Dogan +5

The number of open source language models that can produce Turkish is increasing day by day, as in other languages. In order to create the basic versions of such models, the traini…

cs.CL2024

Türkçe Dil Modellerinin Performans Karşılaştırması Performance Comparison of Turkish Language Models

Eren Dogan, M. Egemen Uzun, Atahan Uz +6

The developments that language models have provided in fulfilling almost all kinds of tasks have attracted the attention of not only researchers but also the society and have enabl…

cs.LG2024★ 19 cited

Theoretical research on generative diffusion models: an overview

Melike Nur Yeğin, Mehmet Fatih Amasyalı

Generative diffusion models showed high success in many fields with a powerful theoretical background. They convert the data distribution to noise and remove the noise back to obta…

cs.CL2024

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…

cs.CL2024

Advancing NLP Models with Strategic Text Augmentation: A Comprehensive Study of Augmentation Methods and Curriculum Strategies

Himmet Toprak Kesgin, Mehmet Fatih Amasyali

This study conducts a thorough evaluation of text augmentation techniques across a variety of datasets and natural language processing (NLP) tasks to address the lack of reliable,…

cs.CL2024

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…

cs.CL2024★ 4 cited

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…

cs.CL2023★ 11 cited

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.…

cs.CL2023★ 2 cited

Developing and Evaluating Tiny to Medium-Sized Turkish BERT Models

Himmet Toprak Kesgin, Muzaffer Kaan Yuce, Mehmet Fatih Amasyali

This study introduces and evaluates tiny, mini, small, and medium-sized uncased Turkish BERT models, aiming to bridge the research gap in less-resourced languages. We trained these…

cs.DL2023

Reviewer Assignment Problem: A Systematic Review of the Literature

Meltem Aksoy, Seda Yanik, Mehmet Fatih Amasyali

Appropriate reviewer assignment significantly impacts the quality of proposal evaluation, as accurate and fair reviews are contingent on their assignment to relevant reviewers. The…

cs.CL2022★ 2 cited

Transformers as Neural Augmentors: Class Conditional Sentence Generation via Variational Bayes

M. Şafak Bilici, Mehmet Fatih Amasyali

Data augmentation methods for Natural Language Processing tasks are explored in recent years, however they are limited and it is hard to capture the diversity on sentence level. Be…

cs.LG2022

A Robust Optimization Method for Label Noisy Datasets Based on Adaptive Threshold: Adaptive-k

Enes Dedeoglu, Himmet Toprak Kesgin, Mehmet Fatih Amasyali

SGD does not produce robust results on datasets with label noise. Because the gradients calculated according to the losses of the noisy samples cause the optimization process to go…

cs.LG2022

Cyclical Curriculum Learning

H. Toprak Kesgin, M. Fatih Amasyali

Artificial neural networks (ANN) are inspired by human learning. However, unlike human education, classical ANN does not use a curriculum. Curriculum Learning (CL) refers to the pr…

cs.SE2020★ 5 cited

Open Source Software Development Challenges: A Systematic Literature Review on GitHub

Abdulkadir Şeker, Banu Diri, Halil Arslan +1

Git is used as the distributed version control system for many open-source software projects. One Git-based service, GitHub, is the most common code hosting and repository service…