14 citations · 33 across the 19 of their papers we have counts for
20 papers
Adapting Reinforcement Learning with Chain-of-Thought Supervision for Explainable Detection of Hateful and Propagandistic Memes
Mohamed Bayan Kmainasi, Mucahid Kutlu, Ali Ezzat Shahroor +2
Hateful and propagandistic memes exploit the interplay between images and text to convey harmful intent that neither modality reveals alone. Although thinking-based multimodal larg…
Can Thinking Models Think to Detect Hateful Memes?
Mohamed Bayan Kmainasi, Mucahid Kutlu, Ali Ezzat Shahroor +2
Hateful memes often require compositional multimodal reasoning: the image and text may appear benign in isolation, yet their interaction conveys harmful intent. Although thinking-b…
Measuring Political Stance and Consistency in Large Language Models
Salah Feras Alali, Mohammad Nashat Maasfeh, Mucahid Kutlu +1
With the incredible advancements in Large Language Models (LLMs), many people have started using them to satisfy their information needs. However, utilizing LLMs might be problemat…
MultiAIGCD: A Comprehensive dataset for AI Generated Code Detection Covering Multiple Languages, Models,Prompts, and Scenarios
Basak Demirok, Mucahid Kutlu, Selin Mergen
As large language models (LLMs) rapidly advance, their role in code generation has expanded significantly. While this offers streamlined development, it also creates concerns in ar…
TurQUaz at CheckThat! 2025: Debating Large Language Models for Scientific Web Discourse Detection
Tarık Saraç, Selin Mergen, Mucahid Kutlu
In this paper, we present our work developed for the scientific web discourse detection task (Task 4a) of CheckThat! 2025. We propose a novel council debate method that simulates s…
NativQA Framework: Enabling LLMs and VLMs with Native, Local, and Everyday Knowledge
Firoj Alam, Md Arid Hasan, Sahinur Rahman Laskar +3
The rapid progress of large language models (LLMs) raises concerns about cultural bias, fairness, and performance in diverse languages and underrepresented regions. Addressing thes…
GenTREC: The First Test Collection Generated by Large Language Models for Evaluating Information Retrieval Systems
Mehmet Deniz Türkmen, Mucahid Kutlu, Bahadir Altun +1
Building test collections for Information Retrieval evaluation has traditionally been a resource-intensive and time-consuming task, primarily due to the dependence on manual releva…
GenAI Content Detection Task 2: AI vs. Human -- Academic Essay Authenticity Challenge
Shammur Absar Chowdhury, Hind Almerekhi, Mucahid Kutlu +5
This paper presents a comprehensive overview of the first edition of the Academic Essay Authenticity Challenge, organized as part of the GenAI Content Detection shared tasks colloc…
AIGCodeSet: A New Annotated Dataset for AI Generated Code Detection
Basak Demirok, Mucahid Kutlu
While large language models provide significant convenience for software development, they can lead to ethical issues in job interviews and student assignments. Therefore, determin…
Detecting Turkish Synonyms Used in Different Time Periods
Umur Togay Yazar, Mucahid Kutlu
Dynamic structure of languages poses significant challenges in applying natural language processing models on historical texts, causing decreased performance in various downstream…
NativQA: Multilingual Culturally-Aligned Natural Query for LLMs
Md. Arid Hasan, Maram Hasanain, Fatema Ahmad +6
Natural Question Answering (QA) datasets play a crucial role in evaluating the capabilities of large language models (LLMs), ensuring their effectiveness in real-world applications…
Turkronicles: Diachronic Resources for the Fast Evolving Turkish Language
Togay Yazar, Mucahid Kutlu, İsa Kerem Bayırlı
Over the past century, the Turkish language has undergone substantial changes, primarily driven by governmental interventions. In this work, our goal is to investigate the evolutio…
I Know You Did Not Write That! A Sampling Based Watermarking Method for Identifying Machine Generated Text
Kaan Efe Keleş, Ömer Kaan Gürbüz, Mucahid Kutlu
Potential harms of Large Language Models such as mass misinformation and plagiarism can be partially mitigated if there exists a reliable way to detect machine generated text. In t…
Catch Me If You Can: Deceiving Stance Detection and Geotagging Models to Protect Privacy of Individuals on Twitter
Dilara Dogan, Bahadir Altun, Muhammed Said Zengin +2
The recent advances in natural language processing have yielded many exciting developments in text analysis and language understanding models; however, these models can also be use…
Embeddings-Based Clustering for Target Specific Stances: The Case of a Polarized Turkey
Ammar Rashed, Mucahid Kutlu, Kareem Darwish +2
On June 24, 2018, Turkey conducted a highly consequential election in which the Turkish people elected their president and parliament in the first election under a new presidential…
Too Many Claims to Fact-Check: Prioritizing Political Claims Based on Check-Worthiness
Yavuz Selim Kartal, Busra Guvenen, Mucahid Kutlu
The massive amount of misinformation spreading on the Internet on a daily basis has enormous negative impacts on societies. Therefore, we need automated systems helping fact-checke…
Embedding-based Qualitative Analysis of Polarization in Turkey
Mucahid Kutlu, Kareem Darwish, Cansin Bayrak +2
On June 24, 2018, Turkey conducted a highly-consequential election in which the Turkish people elected their president and parliament in the first election under a new presidential…
Devam vs. Tamam: 2018 Turkish Elections
Mucahid Kutlu, Kareem Darwish, Tamer Elsayed
On June 24, 2018, Turkey held a historical election, transforming its parliamentary system to a presidential one. One of the main questions for Turkish voters was whether to start…
Correlation and Prediction of Evaluation Metrics in Information Retrieval
Mucahid Kutlu, Vivek Khetan, Matthew Lease
Because researchers typically do not have the time or space to present more than a few evaluation metrics in any published study, it can be difficult to assess relative effectivene…
Efficient Test Collection Construction via Active Learning
Md Mustafizur Rahman, Mucahid Kutlu, Tamer Elsayed +1
To create a new IR test collection at low cost, it is valuable to carefully select which documents merit human relevance judgments. Shared task campaigns such as NIST TREC pool doc…