3 citations · 5 across the 11 of their papers we have counts for
12 papers
AgenticTwin: An Agentic LLM Framework Integrated with Digital Twin for Anomaly Detection
Touseef Hasan, Mounika Ghanta, Souvika Sarkar +1
Digital twins are increasingly used to monitor and simulate the behavior of cyber-physical systems. Even with skilled operators, interpreting anomalies detected within digital twin…
TRACE: Trustworthy Retrieval-Augmented Conversational Engine
Touseef Hasan, Laila Cure, Souvika Sarkar
Public service chatbots are expected to deliver recommendations from an underlying public service directory, while also making sure that the recommendations respect explicit user c…
Knowledge Graph-Enhanced Zero-Shot Topic Classification: A Multi-Strategy Comparative Study
Shahana Akter, Yatharth Vohra, Ankita Shukla +1
Multi-label topic classification without labeled training data is a challenging task, specially when documents contain complex relational information. We present a zero-shot multi-…
SecureRAG-RTL: A Retrieval-Augmented, Multi-Agent, Zero-Shot LLM-Driven Framework for Hardware Vulnerability Detection
Touseef Hasan, Blessing Airehenbuwa, Nitin Pundir +2
Large language models (LLMs) have shown remarkable capabilities in natural language processing tasks, yet their application in hardware security verification remains limited due to…
Retrieval Challenges in Low-Resource Public Service Information: A Case Study on Food Pantry Access
Touseef Hasan, Laila Cure, Souvika Sarkar
Public service information systems are often fragmented, inconsistently formatted, and outdated. These characteristics create low-resource retrieval environments that hinder timely…
Instructional Goal-Aligned Question Generation for Student Evaluation in Virtual Lab Settings: How Closely Do LLMs Actually Align?
R. Alexander Knipper, Indrani Dey, Souvika Sarkar +3
Virtual Labs offer valuable opportunities for hands-on, inquiry-based science learning, yet teachers often struggle to adapt them to fit their instructional goals. Third-party mate…
Investigating Hallucination in Conversations for Low Resource Languages
Amit Das, Md. Najib Hasan, Souvika Sarkar +7
Large Language Models (LLMs) have demonstrated remarkable proficiency in generating text that closely resemble human writing. However, they often generate factually incorrect state…
Pitfalls of Evaluating Language Models with Open Benchmarks
Md. Najib Hasan, Md Mahadi Hassan Sibat, Mohammad Fakhruddin Babar +3
Open Large Language Model (LLM) benchmarks, such as HELM and BIG-Bench, provide standardized and transparent evaluation protocols that support comparative analysis, reproducibility…
Advancing Security with Digital Twins: A Comprehensive Survey
Blessing Airehenbuwa, Touseef Hasan, Souvika Sarkar +1
The proliferation of electronic devices has greatly transformed every aspect of human life, such as communication, healthcare, transportation, and energy. Unfortunately, the global…
Zero-Shot Multi-Label Classification of Bangla Documents: Large Decoders Vs. Classic Encoders
Souvika Sarkar, Md. Najib Hasan, Santu Karmaker
Bangla, a language spoken by over 300 million native speakers and ranked as the sixth most spoken language worldwide, presents unique challenges in natural language processing (NLP…
SimPal: Towards a Meta-Conversational Framework to Understand Teacher's Instructional Goals for K-12 Physics
Effat Farhana, Souvika Sarkar, Ralph Knipper +4
Simulations are widely used to teach science in grade schools. These simulations are often augmented with a conversational artificial intelligence (AI) agent to provide real-time s…
Investigating Annotator Bias in Large Language Models for Hate Speech Detection
Amit Das, Zheng Zhang, Najib Hasan +12
Data annotation, the practice of assigning descriptive labels to raw data, is pivotal in optimizing the performance of machine learning models. However, it is a resource-intensive…