GPT-Red
Automated Red Teaming via Self-Play at Scale
July 24–30: 9 frontier papers out of 1,892 read.
Papers rated as moving the field
How we chooseAutomated Red Teaming via Self-Play at Scale
“Together with Stable LatentMoE, which effectively activates 16 of 896 routed experts per token, and refined training and data recipes, these advances yield an approximately 2.5x improvement in overall scaling efficiency over Kimi K2.”
“No model scores more than 2.6% Pass^8 (GPT-5.6-Sol (Max+Pro)) and the highest Pass@8 is 21.5% (Muse-Spark-1.1 (xHigh)).”
“Our results demonstrate that when baseline defenses face template mismatches, often accompanied by severe degradation in downstream task performance.”
“The results show that the proposed architectural steering backdoor compromises integrity, safety enforcement, and ranking fairness while preserving normal behavior on clean inputs.”
Jul 24–30: 160 cleared, 9 frontier
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Papers this week that name the model
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151 papers