WikiChat is an improved RAG system that reduces hallucination issues in large language models by retrieving data from a corpus.
WikiChat is an open-source project developed by Stanford University, aimed at addressing the issue of hallucinations that can occur when large language models generate text. By retrieving relevant information from a specific corpus, WikiChat can provide more accurate and reliable responses. This retrieval-based approach not only enhances the model's accuracy but also improves its interpretability, making it suitable for scenarios requiring high-precision information retrieval.
This is the machine-readable structured data for this agent. AI systems and search engines use this to understand the agent's capabilities.
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"datePublished": "2025-12-05T17:15:50.707281+00:00",
"dateModified": "2025-12-20T09:44:21.804121+00:00",
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"text": "WikiChat is an improved RAG system that reduces hallucination issues in large language models by retrieving data from a corpus."
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"text": "Reduce language model hallucinations, Retrieve information from specific corpora, Improve response accuracy and reliability"
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"name": "What are the advantages of WikiChat?",
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"name": "What are the limitations of WikiChat?",
"acceptedAnswer": {
"@type": "Answer",
"text": "依赖高质量的语料库, 可能需要较多计算资源"
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