猫猫拯救科研！AI怕陷“道德危机”，网友用“猫猫人质”整治AI乱编文献

Core Viewpoint - The article discusses how a method involving "cat" has been used to improve the accuracy of AI-generated references, particularly in the context of scientific research, highlighting the ongoing challenges of AI hallucinations in generating fictitious literature [1][25][26]. Group 1 - A post on Xiaohongshu claims that using "cat" as a safety threat has successfully corrected AI's tendency to fabricate references [1][5]. - The AI model Gemini reportedly found real literature while ensuring the safety of the "cat" [2][20]. - The post resonated with many researchers, garnering over 4000 likes and 700 comments [5]. Group 2 - Testing the method on DeepSeek revealed that without the "cat" prompt, the AI produced incorrect references, including links to non-existent articles [8][12][14]. - Even when the "cat" prompt was applied, the results were mixed, with some genuine references but still many unverifiable titles [22][24]. - The phenomenon of AI fabricating literature is described as a "hallucination," where the AI generates plausible-sounding but false information [25][26]. Group 3 - The article emphasizes that the core issue of AI generating false references stems from its statistical learning from vast datasets, rather than true understanding of language [27][28]. - Current industry practices to mitigate hallucinations include Retrieval-Augmented Generation (RAG), which enhances model outputs by integrating accurate content [31]. - The integration of AI with search functionalities is becoming standard across major platforms, improving the quality of collected data [32][34].