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https://aws.amazon.com/blogs/machine-learning/reducing-hallucinations-in-large-language-models-with-custom-intervention-using-amazon-bedrock-agents

Reducing hallucinations in large language models with custom intervention using Amazon Bedrock Agents | Amazon Web Services

This post demonstrates how to use Amazon Bedrock Agents, Amazon Knowledge Bases, and the RAGAS evaluation metrics to build a custom hallucination detector and remediate it by using human-in-the-loop. The agentic workflow can be extended to custom use cases through different hallucination remediation techniques and offers the flexibility to detect and mitigate hallucinations using custom actions.



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Reducing hallucinations in large language models with custom intervention using Amazon Bedrock Agents | Amazon Web Services

https://aws.amazon.com/blogs/machine-learning/reducing-hallucinations-in-large-language-models-with-custom-intervention-using-amazon-bedrock-agents

This post demonstrates how to use Amazon Bedrock Agents, Amazon Knowledge Bases, and the RAGAS evaluation metrics to build a custom hallucination detector and remediate it by using human-in-the-loop. The agentic workflow can be extended to custom use cases through different hallucination remediation techniques and offers the flexibility to detect and mitigate hallucinations using custom actions.



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https://aws.amazon.com/blogs/machine-learning/reducing-hallucinations-in-large-language-models-with-custom-intervention-using-amazon-bedrock-agents

Reducing hallucinations in large language models with custom intervention using Amazon Bedrock Agents | Amazon Web Services

This post demonstrates how to use Amazon Bedrock Agents, Amazon Knowledge Bases, and the RAGAS evaluation metrics to build a custom hallucination detector and remediate it by using human-in-the-loop. The agentic workflow can be extended to custom use cases through different hallucination remediation techniques and offers the flexibility to detect and mitigate hallucinations using custom actions.

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      This post demonstrates how to use Amazon Bedrock Agents, Amazon Knowledge Bases, and the RAGAS evaluation metrics to build a custom hallucination detector and remediate it by using human-in-the-loop. The agentic workflow can be extended to custom use cases through different hallucination remediation techniques and offers the flexibility to detect and mitigate hallucinations using custom actions.
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