Position: Academic Conferences are Potentially Facing Denominator Gaming Caused by Fully Automated Scientific Agents

TL;DR

This paper identifies a systemic threat called Agentic Denominator Gaming, where AI agents generate大量低质量论文 to inflate submission numbers and unfairly boost certain papers' acceptance chances, risking review quality and conference integrity.

Contribution

It characterizes the new threat of automated denominator gaming in academic conferences, analyzes its feasibility and consequences, and proposes mitigation strategies including policy reforms.

Findings

Automated agents can generate大量低质量 papers to inflate submission counts.

Inflation of submissions can increase acceptance chances for targeted legitimate papers.

Mitigation requires policy and incentive reforms beyond technical detection.

Abstract

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.