Fact Verification

Reducing LLM Hallucinations with the Agentic Approach: In-Depth Analysis and Practice

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Reducing LLM Hallucinations with the Agentic Approach: In-Depth Analysis and Practice

Click the “blue words” to follow us In the field of artificial intelligence, especially in the application of large language models (LLMs), the phenomenon of hallucination has always been a key issue affecting the reliability and accuracy of the models. Hallucination (How to Eliminate Hallucinations in Large Language Models (LLMs)) refers to the text generated … Read more

FaaF: A Custom Fact Recall Evaluation Framework for RAG Systems

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FaaF: A Custom Fact Recall Evaluation Framework for RAG Systems

Source: DeepHub IMBA This article is about 1000 words long and is recommended to read in 5 minutes. When real information exceeds a few words, the chance of exact matching becomes too slim. In RAG systems, actual fact recall evaluation may face the following issues: There has not been much attention paid to automatically verifying … Read more