Papers by Jinwen He

    1 papers
    LLM Factoscope: Uncovering LLMs’ Factual Discernment through Measuring Inner States (2024.findings-acl)

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    Challenge: Large Language Models (LLMs) produce outputs that deviate from factual reality, especially in sensitive applications such as medical consultation and legal advice.
    Approach: They propose a Siamese network-based model that leverages LLMs’ inner states for factual detection.
    Outcome: The proposed model achieves over 96% accuracy on a custom-collected factual detection dataset.

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