most citedMitigating hallucinations in healthcare LLMs with granular fact-checking and domain-specific adaptation

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV2026

BioAutoML-NAS: An End-to-End AutoML Framework for Multimodal Insect Classification via Neural Architecture Search on Large-Scale Biodiversity Data

Arefin Ittesafun Abian, Debopom Sutradhar, Md Rafi Ur Rashid +5

Insect classification is important for agricultural management and ecological research, as it directly affects crop health and production. However, this task remains challenging du…

cs.CL20261 cited

Mitigating hallucinations in healthcare LLMs with granular fact-checking and domain-specific adaptation

Musarrat Zeba, Abdullah Al Mamun, Kishoar Jahan Tithee +8

In healthcare, it is essential for any Large Language Model (LLM)-generated output to be reliable and accurate, particularly in cases involving decision-making and patient safety.…

cs.CV2026

A Source-Free Approach for Domain Adaptation via Multiview Image Transformation and Latent Space Consistency

Debopom Sutradhar, Md. Abdur Rahman, Mohaimenul Azam Khan Raiaan +2

Domain adaptation (DA) addresses the challenge of transferring knowledge from a source domain to a target domain where image data distributions may differ. Existing DA methods ofte…

cs.CV2025

PPORLD-EDNetLDCT: A Proximal Policy Optimization-Based Reinforcement Learning Framework for Adaptive Low-Dose CT Denoising

Debopom Sutradhar, Ripon Kumar Debnath, Mohaimenul Azam Khan Raiaan +3

Low-dose computed tomography (LDCT) is critical for minimizing radiation exposure, but it often leads to increased noise and reduced image quality. Traditional denoising methods, s…

cs.CV2025

CLAIRE: A Dual Encoder Network with RIFT Loss and Phi-3 Small Language Model Based Interpretability for Cross-Modality Synthetic Aperture Radar and Optical Land Cover Segmentation

Debopom Sutradhar, Arefin Ittesafun Abian, Mohaimenul Azam Khan Raiaan +3

Accurate land cover classification from satellite imagery is crucial in environmental monitoring and sustainable resource management. However, it remains challenging due to the com…