Mehmet Fatih Amasyalı

KFD: Selective Token Filtering and Adaptive Weighting for Efficient Knowledge Distillation

Symmetry

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

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

LLaVa-RS: A Unified Model for Image and Change Captioning in Remote Sensing

Turkuaz-RAG — A Turkish Multi-Context Retrieval Benchmark

A fast approach for flood mapping over a large region using Sentinel-2 imagery

Remote Sensing Letters

A cyclical loss-based optimization algorithm for pretraining LLMs on noisy data

Knowledge-Based Systems

Scalable Remote Sensing Image Change Captioning using In-Context Learning

Turkish-e5: E5 Model Enhanced for Turkish with Multi-Positive Contrastive Learning

Creating a Large Clean Web Corpus for Turkish

Improving Information Retrieval in Turkish: A ColBERT-Based Approach

EAI/Springer Innovations in Communication and Computing

Robustness of emotion recognition in dialogue systems: A study on third-party API integrations and black-box attacks

Speech Communication

Optimal RAG System Design for Turkish Textbooks: A Comprehensive Evaluation and Performance Enhancement Study

Multimodal LLM Guidance for Aligning Text-to-Image Generation

Communications in computer and information science

Advancing NLP models with strategic text augmentation: A comprehensive study of augmentation methods and curriculum strategies

Natural Language Processing Journal

Generative diffusion models: A survey of current theoretical developments

Neurocomputing

From text to multimodal: a survey of adversarial example generation in question answering systems

Knowledge and Information Systems

Optimizing Large Language Models for Turkish: New Methodologies in Corpus Selection and Training

Data Augmentation in Remote Sensing Image Change Captioning

Enhancing Retrieval-Augmented Generation Accuracy with Dynamic Chunking and Optimized Vector Search

Orclever Proceedings of Research and Development

Cosmos-LLaVA: Chatting with the Visual