今年ICLR有救了！120篇论文实测，换种写法AI真会涨分

TL;DR - A controlled study of 120 ICLR 2026 submissions finds that AI reviewers can assign meaningfully different scores when the underlying research stays fixed but its rhetoric changes. Quantitative-evidence presentation, novelty framing, and claim scope had the strongest and most consistent effects.

• The study generated 4,200 paper variants and collected 42,396 reviews from five AI reviewer models under standard and strict review prompts.
• Strengthening the presentation of existing quantitative evidence raised scores by up to 0.93 points in one configuration; positive versus negative framing changed weak-accept-or-better rates by 13 percentage points.
• Positive framing outscored negative framing for novelty, evidence, and scope in 117, 116, and 113 of 120 papers, respectively, while lexical and syntactic complexity showed little consistent benefit.
• Stricter prompts lowered average scores by 1.36 points but did not systematically reduce rhetorical sensitivity; gains also varied substantially by rewriting–reviewer model pairing.