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# Identifying Low-Quality Textual Content using LLMs
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We explore the feasibility of utilizing Large Language Models (LLMs) to identify 'BS'—text that is of low quality or lacks meaningful content. While recognizing the inherent challenges in detecting AI-generated text with absolute certainty, this research focuses on the more attainable goal of identifying text that is substantively empty or devoid of content.
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Can Large Language Models (LLMs) detect low quality text?. We do this by finding text that can "suprise" the model.
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## Theoretical Underpinnings
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