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

1 citations · 1 across the 4 of their papers we have counts for

collaborators

10 papers

cs.CV2026

Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach

Wasimul Karim, Nur Mohammad Fahad, Abdul Hasib Siddique +4

Accurate segmentation of electrolyzer materials is essential for automated disassembly, sustainable recycling, and circular manufacturing in hydrogen technologies. However, this ta…

cs.CV2026

A Physics-Informed, Behavior-Aware Digital Twin for Robust Multimodal Forecasting of Core Body Temperature in Precision Livestock Farming

Riasad Alvi, Mohaimenul Azam Khan Raiaan, Sadia Sultana Chowa +6

Precision livestock farming requires accurate and timely heat stress prediction to ensure animal welfare and optimize farm management. This study presents a physics-informed digita…

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

Learning to Weigh Waste: A Physics-Informed Multimodal Fusion Framework and Large-Scale Dataset for Commercial and Industrial Applications

Md. Adnanul Islam, Wasimul Karim, Md Mahbub Alam +7

Accurate weight estimation of commercial and industrial waste is important for efficient operations, yet image-based estimation remains difficult because similar-looking objects ma…

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…