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# Identifying Low-Quality Textual Content using LLMs
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.
Can Large Language Models (LLMs) detect low quality text?. We do this by finding text that can "suprise" the model.
## Theoretical Underpinnings