collaborators

10 papers

cs.CL2026

From Automation to Collaboration: Human-in-the-Loop Methods for Safe and Trustworthy NLP

Most. Sharmin Sultana Samu, MD. Tanvir Ahmed Seum, Md. Rakibul Islam

Large language models are widely deployed in high-stakes NLP tasks, yet risks such as bias, hallucination, adversarial vulnerability and unreliable generalization remain. Probe-bas…

cs.CV2026

A Two-Stage Multitask Vision-Language Framework for Explainable Crop Disease Visual Question Answering

Md. Zahid Hossain, Most. Sharmin Sultana Samu, Md. Rakibul Islam +1

Visual question answering (VQA) for crop disease analysis requires accurate visual understanding and reliable language generation. In this work, we present a lightweight and explai…

cs.HC2026

AI as Teammate or Tool? A Review of Human-AI Interaction in Decision Support

Most. Sharmin Sultana Samu, Nafisa Khan, Kazi Toufique Elahi +3

The integration of Artificial Intelligence (AI) necessitates determining whether systems function as tools or collaborative teammates. In this study, by synthesizing Human-AI Inter…

cs.CL2025

Detecting AI-Generated Paraphrases in Bengali: A Comparative Study of Zero-Shot and Fine-Tuned Transformers

Md. Rakibul Islam, Most. Sharmin Sultana Samu, Md. Zahid Hossain +2

Large language models (LLMs) can produce text that closely resembles human writing. This capability raises concerns about misuse, including disinformation and content manipulation.…

cs.SD2025

Zero-Shot to Zero-Lies: Detecting Bengali Deepfake Audio through Transfer Learning

Most. Sharmin Sultana Samu, Md. Rakibul Islam, Md. Zahid Hossain +2

The rapid growth of speech synthesis and voice conversion systems has made deepfake audio a major security concern. Bengali deepfake detection remains largely unexplored. In this w…

cs.CV2025

FUSE: Unifying Spectral and Semantic Cues for Robust AI-Generated Image Detection

Md. Zahid Hossain, Most. Sharmin Sultana Samu, Md. Kamrozzaman Bhuiyan +2

The fast evolution of generative models has heightened the demand for reliable detection of AI-generated images. To tackle this challenge, we introduce FUSE, a hybrid system that c…