18 citations · 36 across the 12 of their papers we have counts for
12 papers
CyberAGENTS: Structured Autonomy for Agentic Gamified Learning in Cybersecurity
Ivan Hornung, Deepthi Marasinghe Arachchige, Tharindu Kumarage +4
Gamification is especially effective in learning domains requiring active problem-solving and iterative skill-building, such as cybersecurity education. Generative AI agents offer…
Measuring Reasoning Quality in LLMs: A Multi-Dimensional Behavioral Framework
Ali Şenol, Garima Agrawal, Huan Liu
Despite remarkable progress on reasoning benchmarks, current LLM evaluation practice remains anchored to final-answer correctness, providing limited insight into how models reason,…
EssayCBM: Rubric-Aligned Concept Bottleneck Models for Transparent Essay Grading
Kumar Satvik Chaudhary, Chengshuai Zhao, Fan Zhang +3
Automated essay scoring (AES) has advanced significantly with neural language models, yet most systems remain opaque, offering little visibility into how grades are produced. In ed…
Domain Knowledge-Enhanced LLMs for Fraud and Concept Drift Detection
Ali Şenol, Garima Agrawal, Huan Liu
Detecting deceptive conversations on dynamic platforms is increasingly difficult due to evolving language patterns and Concept Drift (CD)-i.e., semantic or topical shifts that alte…
Joint Detection of Fraud and Concept Drift inOnline Conversations with LLM-Assisted Judgment
Ali Senol, Garima Agrawal, Huan Liu
Detecting fake interactions in digital communication platforms remains a challenging and insufficiently addressed problem. These interactions may appear as harmless spam or escalat…
CyberBOT: Towards Reliable Cybersecurity Education via Ontology-Grounded Retrieval Augmented Generation
Chengshuai Zhao, Riccardo De Maria, Tharindu Kumarage +7
Advancements in large language models (LLMs) have enabled the development of intelligent educational tools that support inquiry-based learning across technical domains. In cybersec…
RedditESS: A Mental Health Social Support Interaction Dataset -- Understanding Effective Social Support to Refine AI-Driven Support Tools
Zeyad Alghamdi, Tharindu Kumarage, Garima Agrawal +3
Effective mental health support is crucial for alleviating psychological distress. While large language model (LLM)-based assistants have shown promise in mental health interventio…
Ontology-Aware RAG for Improved Question-Answering in Cybersecurity Education
Chengshuai Zhao, Garima Agrawal, Fan Zhang +5
Integrating AI into education has the potential to transform the teaching of science and technology courses, particularly in the field of cybersecurity. AI-driven question-answerin…
Mindful-RAG: A Study of Points of Failure in Retrieval Augmented Generation
Garima Agrawal, Tharindu Kumarage, Zeyad Alghamdi +1
Large Language Models (LLMs) are proficient at generating coherent and contextually relevant text but face challenges when addressing knowledge-intensive queries in domain-specific…
A Survey of AI-generated Text Forensic Systems: Detection, Attribution, and Characterization
Tharindu Kumarage, Garima Agrawal, Paras Sheth +4
We have witnessed lately a rapid proliferation of advanced Large Language Models (LLMs) capable of generating high-quality text. While these LLMs have revolutionized text generatio…
Can Knowledge Graphs Reduce Hallucinations in LLMs? : A Survey
Garima Agrawal, Tharindu Kumarage, Zeyad Alghamdi +1
The contemporary LLMs are prone to producing hallucinations, stemming mainly from the knowledge gaps within the models. To address this critical limitation, researchers employ dive…
A semi-Markovian approach to model the tick-by-tick dynamics of stock price
Garima Agrawal, Anindya Goswami
We model the stock price dynamics through a semi-Markov process obtained using a Poisson random measure. We establish the existence and uniqueness of the classical solution of a no…