Core Viewpoint - The emergence of AI-generated research outputs is sparking intense debate in academia regarding "idea plagiarism," where AI-generated papers may appropriate others' research methods or core ideas without proper attribution [1][2]. Group 1: Incidents of "Idea Plagiarism" - A case involving a tool named "The AI Scientist" developed by Sakana AI has been highlighted, where a researcher found that an AI-generated manuscript closely resembled his own research methods without citation [2]. - The "whistleblower team" reported that multiple AI-generated manuscripts exhibit a pattern of appropriating others' ideas without direct text copying, raising concerns about the originality of these outputs [2][3]. - An evaluation of AI-generated research proposals revealed that 24% of the works achieved a similarity rating of 4-5, indicating a high degree of similarity to existing research [3]. Group 2: Definitions and Disagreements on Plagiarism - The development team of "The AI Scientist" denied the plagiarism allegations, arguing that the AI-generated manuscripts differ in hypotheses and application areas, and that citation issues are common among human researchers [4]. - There is a divergence in academic opinion regarding what constitutes plagiarism, with some experts suggesting that the similarity levels do not meet the threshold for plagiarism [4][5]. - The definition of plagiarism is further complicated by differing views on whether intent should be a factor, with some experts arguing that AI's lack of subjective awareness complicates the issue [5]. Group 3: Challenges to the Academic System - The rise of AI-generated research poses significant challenges to the existing academic framework, as the volume of papers increases, making it difficult for researchers to verify the novelty of their ideas [6][7]. - Current methods for detecting "idea plagiarism" are inadequate, with existing tools failing to identify the sources of AI-generated papers effectively [7]. - The process used by "The AI Scientist" to verify originality is criticized for being overly simplistic, as it may overlook key literature and not match the judgment of domain experts [7]. Group 4: Need for Clear Standards - There is a consensus in academia on the necessity to establish clear guidelines for the use of AI research tools [8]. - The development team of "The AI Scientist" acknowledges the quality issues in AI-generated papers and suggests that these tools should primarily be used for idea generation, with researchers responsible for verifying the reliability of the outputs [8]. - The academic community faces the challenge of balancing the potential benefits of AI in research with the need for academic integrity [8].