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Study finds LLMs can identify their own mistakes
It turns out that LLMs encode quite a bit of knowledge about the truthfulness of their answers, even when they give the wrong one.
The researchers conducted their experiments on four variants of Mistral 7B and Llama 2 models across 10 datasets spanning various tasks, including question answering, natural language inference, math problem-solving, and sentiment analysis. “These patterns are consistent across nearly all datasets and models, suggesting a general mechanism by which LLMs encode and process truthfulness during text generation,” the researchers write. This finding suggests that current evaluation methods, which solely rely on the final output of LLMs, may not accurately reflect their true capabilities.
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