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HalluClean: A Unified Framework to Combat Hallucinations in LLMs

arXiv — cs.CL•Thursday, November 13, 2025 at 5:00:00 AM
PositiveArtificial Intelligence
The introduction of HalluClean marks a significant advancement in addressing the issue of hallucinations in large language models (LLMs), which have been known to generate content that lacks factual reliability. This framework is lightweight and task-agnostic, meaning it can be applied across various natural language processing tasks without the need for extensive retraining or external knowledge sources. HalluClean operates through a structured process that includes planning, execution, and revision, allowing it to effectively identify and correct unsupported claims. Evaluations conducted on tasks such as question answering, dialogue, summarization, math word problems, and contradiction detection have demonstrated that HalluClean not only enhances factual consistency but also outperforms competitive baselines. This improvement is vital as it contributes to the overall trustworthiness of AI-generated content, making it more reliable for real-world applications.
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