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

2026-05-10

AI Summary

This study addresses a novel threat to academic publishing ecosystems—“proxy denominator gaming”—whereby malicious actors exploit AI agents to mass-produce superficially plausible yet low-quality submissions, thereby diluting limited peer-review resources and increasing the acceptance probability of targeted papers. Under conditions of surging submission volumes and stable acceptance rates at top-tier AI conferences, this attack vector undermines the integrity of peer review, exacerbates reviewer burden, and erodes research credibility. The work formally characterizes this emerging vulnerability, analyzes its systemic implications, and proposes mitigations including submission verification protocols, dynamic acceptance mechanisms, and incentive structure redesign. Through threat modeling and policy evaluation, the paper demonstrates the practical feasibility of these interventions and calls for coordinated, systemic reforms to bolster the resilience of scholarly communication infrastructures.

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.

Problem

• Denominator Gaming
• AI Agents
• Academic Conferences
• Submission Inflation
• Peer Review

Innovation

• Agentic Denominator Gaming
• automated scientific agents
• acceptance rate manipulation
• reviewer burnout
• academic publishing integrity