SelfCheckGPT detects hallucinations by checking consistency across multiple sampled responses from black-box LLMs on WikiBio biography generation tasks.
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2 Pith papers cite this work, alongside 155 external citations. Polarity classification is still indexing.
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Gopher, a 280 billion parameter language model, achieves state-of-the-art performance on the majority of 152 tasks with largest gains in reading comprehension, fact-checking, and toxic language detection.
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SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models
SelfCheckGPT detects hallucinations by checking consistency across multiple sampled responses from black-box LLMs on WikiBio biography generation tasks.
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Scaling Language Models: Methods, Analysis & Insights from Training Gopher
Gopher, a 280 billion parameter language model, achieves state-of-the-art performance on the majority of 152 tasks with largest gains in reading comprehension, fact-checking, and toxic language detection.