Causal Prompting Framework Mitigates Hallucinations in Long-Context LLMs

This research introduces a plug-and-play framework, CIP, designed to address the critical issue of hallucinations in Large Language Models (LLMs), particularly when processing lengthy context. The framework's causal prompting approach offers a promising method for improving the reliability and trustworthiness of LLM outputs.

• •CIP is a framework designed to reduce hallucinations in LLMs.
• •The framework employs a causal prompting approach.
• •The research focuses on mitigating issues in long-context scenarios.