AI代理批量生成低质论文，人为抬高投稿量以提升特定论文录用率。
Position: Academic Conferences are Potentially Facing Denominator Gaming Caused by Fully Automated Scientific Agents
- 用AI生成大量表面合理但质量差的论文，抬高投稿总数。
- 在固定接受率下，稀释评审压力，提高少数目标论文录用概率。
- 适合关注学术诚信与会议机制安全的研究者阅读。
顶级人工智能会议虽投稿量呈指数增长，但维持相对稳定的接受率，这一隐含政策带来结构性漏洞。本文提出一种新型系统性威胁——‘代理分母游戏’：恶意行为者利用AI代理生成并提交大量看似合理却质量低劣的论文。其目的并非让这些低质论文被接收，而是通过增加投稿总数来稀释评审资源，从而在稳定接受率下，系统性提升少量目标论文的发表概率。我们分析了该威胁的实际可行性及其广泛影响，包括审稿人过劳、评审质量下降，以及自动化论文工厂的兴起。最后，我们评估多种缓解策略，主张长期防护需依赖系统性政策与激励机制改革，而非仅靠技术检测。
原文摘要 · Abstract (English)
The implicit policy of maintaining relatively stable acceptance rates at top AI conferences, despite exponentially growing submissions, introduces a critical structural vulnerability. This position paper characterizes a new systemic threat we term Agentic Denominator Gaming, in which a malicious actor deploys AI agents to generate and submit a large volume of superficially plausible but low-quality papers. Crucially, their objective is not the acceptance of low-quality papers, but rather to inflate the submission denominator and overwhelm reviewing capacity. Under a relatively stable acceptance rate, this dilution can systematically increase the publication probability of a small, targeted set of legitimate papers. We analyze the practical feasibility of this threat and its broader consequences, including intensified reviewer burnout, degraded review quality, and the emergence of industrialized automated agent mills. Finally, we propose and evaluate a range of mitigation strategies, and argue that durable protection will require system-level policy and incentive reforms, rather than relying primarily on technical detection alone.
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