<p class="jove_content">This study presents a lightweight framework for reducing hallucinations in large language models through claim-level verification and adaptive statistical thresholding. By selectively correcting unsupported claims using Natural Language Inference, the approach improves factual accuracy while maintaining low response latency and practical deployment efficiency.</p>

adaptive-nli-driven-claim-verification-with-statistical-decision

Adaptive NLI-Driven Claim Verification with Statistical Decision Modeling for Low-Latency Hallucination Reduction in Large Language Models

Large Language Models (LLMs) exhibit a critical tendency to generate factually incorrect yet linguistically fluent outputs - a phenomenon termed ...

<p class="jove_content">The goal of the VDNABDS protocol is to enhance cloud security by using DNA-based encryption techniques to generate fast, unbreakable keys. It aims to protect sensitive data against brute-force and quantum attacks while ensuring high performance, scalability, and seamless integration with modern cloud systems.</p>

vdnabds-dna-based-cryptographic-protocol-for-enhancing-cloud

VDNABDS, A DNA-Based Cryptographic Protocol for Enhancing Cloud Security

Modern cloud storage systems often struggle to balance security and performance-strong encryption tends to slow down operations, while faster solutions ...

Institution - Odisha University of Technology and Research

Articles Published in JoVE