51 citations · 157 across the 13 of their papers we have counts for
14 papers
When Citations Mislead? A Claim-Level Benchmark for Legal Hallucination Detection
M. Mikail Demir, M. Abdullah Canbaz
Large language models are increasingly used in legal research and drafting, but they can still produce claims that sound convincing without being supported by the cited source. We…
Validate Your Authority: Benchmarking LLMs on Multi-Label Precedent Treatment Classification
M. Mikail Demir, M. Abdullah Canbaz
Automating the classification of negative treatment in legal precedent is a critical yet nuanced NLP task where misclassification carries significant risk. To address the shortcomi…
Who Coordinates U.S. Cyber Defense? A Co-Authorship Network Analysis of Joint Cybersecurity Advisories (2024--2025)
M. Abdullah Canbaz, Hakan Otal, Tugce Unlu +2
Cyber threats increasingly demand joint responses, yet the organizational dynamics behind multi-agency cybersecurity collaboration remain poorly understood. Understanding who leads…
Modeling Bias Evolution in Fashion Recommender Systems: A System Dynamics Approach
Mahsa Goodarzi, M. Abdullah Canbaz
Bias in recommender systems not only distorts user experience but also perpetuates and amplifies existing societal stereotypes, particularly in sectors like fashion e-commerce. Thi…
LegalGuardian: A Privacy-Preserving Framework for Secure Integration of Large Language Models in Legal Practice
M. Mikail Demir, Hakan T. Otal, M. Abdullah Canbaz
Large Language Models (LLMs) hold promise for advancing legal practice by automating complex tasks and improving access to justice. However, their adoption is limited by concerns o…
A New Perspective on ADHD Research: Knowledge Graph Construction with LLMs and Network Based Insights
Hakan T. Otal, Stephen V. Faraone, M. Abdullah Canbaz
Attention-Deficit/Hyperactivity Disorder (ADHD) is a challenging disorder to study due to its complex symptomatology and diverse contributing factors. To explore how we can gain de…
Heuristics and Biases in AI Decision-Making: Implications for Responsible AGI
Payam Saeedi, Mahsa Goodarzi, M Abdullah Canbaz
We investigate the presence of cognitive biases in three large language models (LLMs): GPT-4o, Gemma 2, and Llama 3.1. The study uses 1,500 experiments across nine established cogn…
Analysis of Gene Regulatory Networks from Gene Expression Using Graph Neural Networks
Hakan T. Otal, Abdulhamit Subasi, Furkan Kurt +2
Unraveling the complexities of Gene Regulatory Networks (GRNs) is crucial for understanding cellular processes and disease mechanisms. Traditional computational methods often strug…
Enhancing Mental Health Support through Human-AI Collaboration: Toward Secure and Empathetic AI-enabled chatbots
Rawan AlMakinah, Andrea Norcini-Pala, Lindsey Disney +1
Access to mental health support remains limited, particularly in marginalized communities where structural and cultural barriers hinder timely care. This paper explores the potenti…
LLM Honeypot: Leveraging Large Language Models as Advanced Interactive Honeypot Systems
Hakan T. Otal, M. Abdullah Canbaz
The rapid evolution of cyber threats necessitates innovative solutions for detecting and analyzing malicious activity. Honeypots, which are decoy systems designed to lure and inter…
Federated Learning in Adversarial Environments: Testbed Design and Poisoning Resilience in Cybersecurity
Hao Jian Huang, Hakan T. Otal, M. Abdullah Canbaz
This paper presents the design and implementation of a Federated Learning (FL) testbed, focusing on its application in cybersecurity and evaluating its resilience against poisoning…
Harnessing Deep Learning and Satellite Imagery for Post-Buyout Land Cover Mapping
Hakan T. Otal, Elyse Zavar, Sherri B. Binder +2
Environmental disasters such as floods, hurricanes, and wildfires have increasingly threatened communities worldwide, prompting various mitigation strategies. Among these, property…
LLM-Assisted Crisis Management: Building Advanced LLM Platforms for Effective Emergency Response and Public Collaboration
Hakan T. Otal, M. Abdullah Canbaz
Emergencies and critical incidents often unfold rapidly, necessitating a swift and effective response. In this research, we introduce a novel approach to identify and classify emer…
User characterization for online social networks
Tayfun Tuna, Esra Akbas, Ahmet Aksoy +4
Online social network analysis has attracted great attention with a vast number of users sharing information and availability of APIs that help to crawl online social network data.…