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You can find it in arxiv This study focuses on the comparative analysis. Hallucinations are words generated by the model that are not supported by the source input

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Deep learning based generation is prone to hallucinate unintended text Despite the uniform architecture, transformer models vary considerably in their specific capabilities and performance characteristics It isn't necessarily restricted to a person's.

Natural language inference (nli) involves deciding if a hypothesis is logically supported by a premise. simply put, it's about figuring out if a given statement (the hypothesis) is true based.

The issue is model has a lot of hallucinations on predictions, even in the prompt portion While the same model generates almost perfectly when loaded externally and making predictions using.