11 papers
Quantum Key Distribution Secured Federated Learning for Channel Estimation and Radar Spectrum Sensing in 6G Networks
Ferhat Ozgur Catak, Murat Kuzlu, Jungwon Seo +1
This paper presents a federated learning framework secured by quantum key distribution (QKD) for wireless channel estimation and radar spectrum sensing in the next generation netwo…
Federated Inference: Toward Privacy-Preserving Collaborative and Incentivized Model Serving
Jungwon Seo, Ferhat Ozgur Catak, Chunming Rong +1
Federated Inference (FI) studies how independently trained and privately owned models can collaborate at inference time without sharing data or model parameters. While recent work…
Logit-Level Uncertainty Quantification in Vision-Language Models for Histopathology Image Analysis
Betul Yurdem, Ferhat Ozgur Catak, Murat Kuzlu +1
Vision-Language Models (VLMs) with their multimodal capabilities have demonstrated remarkable success in almost all domains, including education, transportation, healthcare, energy…
EvalQReason: A Framework for Step-Level Reasoning Evaluation in Large Language Models
Shaima Ahmad Freja, Ferhat Ozgur Catak, Betul Yurdem +1
Large Language Models (LLMs) are increasingly deployed in critical applications requiring reliable reasoning, yet their internal reasoning processes remain difficult to evaluate sy…
Trustworthy Quantum Machine Learning: A Roadmap for Reliability, Robustness, and Security in the NISQ Era
Ferhat Ozgur Catak, Jungwon Seo, Umit Cali
Quantum machine learning (QML) is a promising paradigm for tackling computational problems that challenge classical AI. Yet, the inherent probabilistic behavior of quantum mechanic…
Comparative Analysis of Attention Mechanisms for Automatic Modulation Classification in Radio Frequency Signals
Ferhat Ozgur Catak, Murat Kuzlu, Umit Cali
Automatic Modulation Classification (AMC) is a critical component in cognitive radio systems and spectrum management applications. This study presents a comprehensive comparative a…