Prompt-Guided Internal States for Hallucination Detection of Large Language Models (2025.acl-long)
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| Challenge: | Large Language Models (LLMs) generate incorrect or logically incorrect responses, which is known as LLM hallucinations. |
| Approach: | They propose a framework for supervised hallucination detection using in-domain data by prompting changes to the structure related to text truthfulness in LLMs’ internal states. |
| Outcome: | The proposed framework enhances the cross-domain generalization of existing hallucination detection methods. |
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