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有人认为，arXiv 对因单一引用虚构实施的一年禁令，是维护学术诚信的有力举措。 arXiv 是一项特权而非权利，对提交未经核实的内容采取惩戒，有助于提高整体质量标准。

也有人认为这一政策过于严厉、方向错误：arXiv 的提交本就未经严格审查，而同行评审本身也有选择性。单一引用错误不等同于欺诈，也不能代表整篇工作的水平。

判断为欺诈需要有欺骗意图或对真相的鲁莽无视。单一引用的虚构，尤其是可能由合著者或 AI 工具在作者不知情的情况下插入的情况，更可能是疏忽而非蓄意欺骗。

与此同时，很多人强调，不论内容如何生成，作者对其提交的材料负全部责任。未能核实参考文献的存在是根本性的失职，会损毁整篇论文的可信度。

有人认为，这项政策是有效的启发式手段，能防止大量低质量的"草稿"进入存档。若作者连基本的参考文献核对都做不到，其它部分也难以令人信服。

另有建议认为，在允许在 arXiv 发布前要求同行评审是一种折中做法，可促使以往提交过未经核实内容的作者提高严谨性。

批评者则警告，政策可能被不公平地执行，例如当合著者在他人不知情的情况下添加了虚假引用时，责任归属和 arXiv 能否正确调查个人责任都成问题。

有人担心，该政策会惩罚那些在时间压力下犯下真诚错误的研究者，而对有意欺诈的人则威慑有限，因为他们可能会更善于掩盖自己的疏忽。

也有观点认为，这是代价极小却见效的改进：通过自动化工具验证参考文献存在性并不难，能过滤掉最明显的疏忽，不会给认真的作者带来负担。

更广泛的背景是，引用准确性的问题在 AI 出现之前就已长期存在，但大型语言模型大幅增加了这类风险，因此自动化检测和更严格的政策被视为维护科研记录可信度的必要手段。

总的讨论呈现出两种鲜明对立的观点：一方面有人认为 arXiv 的政策是捍卫下滑科学标准的必需措施，另一方面有人认为这对可能是无心之失的研究者过于苛刻。普遍达成的共识是，核实参考文献是学术工作不可妥协的最低要求；但对于单一引用虚构是否应定性为欺诈还是仅为疏忽、作者责任的范围、 AI 作为工具还是拐杖的角色以及如何公平执行此类政策，仍存在显著分歧。尽管大多数人同意必须采取措施应对低质量提交，但对具体制裁的严厉程度和实施方式仍有争议。 • A one-year arXiv ban for a single hallucinated citation is seen by some as a strong positive for scientific integrity, as arXiv is a privilege, not a right, and enforcing consequences for submitting unverified content raises the bar for quality.

• Others argue the policy is excessive and misguided, noting that arXiv submissions are not rigorously checked, peer review is far more selective, and a single citation error does not indicate fraud or reflect the overall quality of the work.

• Fraud requires intent to deceive or reckless disregard, and a single hallucinated citation, especially if inserted by a co-author or AI tool without the author's knowledge, may constitute carelessness rather than fraud.

• Many emphasize that authors bear full responsibility for their submissions, regardless of how content is generated, and failing to verify that cited references exist is a fundamental failure that undermines the credibility of the entire paper.

• Some defend the policy as a reasonable heuristic against low-effort "slop" submissions, arguing that if authors cannot perform the basic task of checking references, the rest of their work cannot be trusted either.

• The requirement that future submissions be peer-reviewed before arXiv posting is viewed as a proportionate response, ensuring that authors who previously submitted unvetted work demonstrate improved rigor.

• Critics warn that the policy may be applied unevenly, such as when a co-author adds a fraudulent citation without others' knowledge, raising questions about fairness and arXiv's ability to investigate individual responsibility.

• There is concern that the policy could discourage honest researchers who make genuine mistakes, particularly under time pressure, while doing little to deter deliberate fraudsters who would simply disguise their sloppiness.

• Some suggest the policy is a modest but cost-free improvement, as automated tools can easily verify reference existence, filtering out only the most negligent submissions without burdening careful authors.

• The broader context includes longstanding issues with citation accuracy predating AI, but LLMs have dramatically increased the risk, making automated detection and stricter policies necessary to maintain trust in the scientific record.

The discussion reveals a sharp divide between those who view arXiv's policy as a necessary defense against declining scientific standards and those who see it as a disproportionate punishment for what may be an honest mistake. A strong consensus exists that verifying references is a non-negotiable minimum for academic work, but there is significant disagreement over whether a single hallucinated citation constitutes evidence of fraud or mere negligence. The debate also touches on questions of authorial responsibility, the role of AI as a tool versus a crutch, and the practical challenges of enforcing such policies fairly across co-authored works. While most agree that something must be done to address the flood of low-quality submissions, the severity and implementation of this particular sanction remain contested.