A scalable framework for evaluating multiple language models through cross-domain generation and hallucination detection

A scalable framework for evaluating multiple language models through cross-domain generation and hallucination detection

Abstract Large language models (LLMs) have significantly advanced in recent years, greatly enhancing the capabilities of retrieval-augmented generation (RAG) systems. However, challenges such as semantic similarity, bias/sentiment, and hallucinations persist, especially in domain-specific applicatio...

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Bibliographic Details
Main Authors: Sorup Chakraborty, Rajesh Chowdhury, Sourov Roy Shuvo, Rajdeep Chatterjee, Satyabrata Roy
Format: Article
Language:English
Published: Nature Portfolio 2025-08-01
Series:Scientific Reports
Subjects:
Large Language Models (LLMs)
Retrieval-Augmented Generation (RAG)
Semantic Similarity
Bias Detection
Hallucination Detection
Multi-Domain Benchmarking
Online Access:https://doi.org/10.1038/s41598-025-15203-5
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https://doi.org/10.1038/s41598-025-15203-5

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