The literature already proposes several distinctions between types of false outputs (e.g., hallucination, confabulation, strategic deception). However, current lie‑detection methods often evaluate detectors on datasets that do not cleanly separate these mechanisms, which makes it difficult to know what the detector is actually detecting.
When LLMs produce false statements, how often are these due to epistemic failure versus incentive‑driven misreporting?
If you are inspired by this idea, you can reach out to the authors for collaboration or cite it:
@misc{bai-detect-different-lies-2026,
author = {Bai, Xiaoyan},
title = {Detect different lies},
year = {2026},
url = {https://hypogenic.ai/ideahub/idea/71I2Dggyhxj7r4VgKWwr}
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