1 citations · 1 across the 1 of their papers we have counts for
2 papers
cs.CL2026★ 1 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.CL2025
Hallucination to Truth: A Review of Fact-Checking and Factuality Evaluation in Large Language Models
Subhey Sadi Rahman, Md. Adnanul Islam, Md. Mahbub Alam +5
Large Language Models (LLMs) are trained on vast and diverse internet corpora that often include inaccurate or misleading content. Consequently, LLMs can generate misinformation, m…