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"It doesn't" depends on specific implementation. "It can't" is wrong. https://arxiv.org/abs/2404.15993 https://arxiv.org/abs/2404.15993 "Uncertainty Estimation
by viraptor 2y ago
"It doesn't" depends on specific implementation. "It can't" is wrong. https://arxiv.org/abs/2404.15993 https://arxiv.org/abs/2404.15993 "Uncertainty Estimation and Quantification for LLMs: A Simple Supervised Approach (...) our method is easy to implement and adaptable to different levels of model accessibility including black box, grey box, and white box. "
- andrewmcwatters 2y agoIt can't is technically correct, and the paper you link explicitly states that it outlines an _external_ system utilizing _labeled data_. So, no, current models can't. You always need an external system for verifiability.
- viraptor 2y agoIt's trained on labelled data - to figure out how to interpret the LLM. But the external system is used only to interpret the hidden states already present in the analysed network. That means the original LLM already contains the "knows/doesn't" signal. It's just not output by default.
- HarHarVeryFunny 2y ago"By looking at different wrong answers generated by the LLM, we note that although our approach sometimes gives a high confidence score on a wrong answer generated by the LLM, at other times it shows desirable properties such as giving higher uncertainty scores to better answers, and giving low confidence score when LLM does not know the answer."