Papers with truthfulness detector

    1 papers
    AI-LieDar : Examine the Trade-off Between Utility and Truthfulness in LLM Agents (2025.naacl-long)

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    Challenge: LieDar is a framework to study how LLM-based agents navigate these scenarios in a multi-turn interactive setting.
    Approach: They propose a framework to study how LLM-based agents navigate these scenarios in an interactive multi-turn setting.
    Outcome: The proposed framework shows that all models are truthful less than 50% of the time, although truthfulness and goal achievement rates vary across models.

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