📣 Variation in Verification: Understanding Verification Dynamics in Large Language Models 📄 Paper: 🔗 Project: Ever wonder if your LLM verifier is actually reliable for your task? Our analysis framework reveals three key factors that determine verification success across problem difficulty, generator capability, and verifier capability. Key insights: 📈 Problem difficulty drives correct response recognition - verifiers excel on easy problems but struggle with hard ones 🔍 Generator strength affects error detection - weak generators produce obvious mistakes, strong ones create elegant but wrong solutions ⚖️ Verifier scaling shows diminishing returns in certain regimes - sometimes GPT-4o barely beats smaller models 💡 For test-time scaling: weak generators + verification can match strong generators' performance, and expensive verifiers aren't always worth it. Great work by Yefan Zhou @LiamZhou98, Austin Xu @austinsxu, Yilun Zhou @YilunZhou, Janvijay Singh @iamjanvijay, Jiang Gui @JiangGui, Shafiq Joty @JotyShafiq! #LLM #AIVerification #TestTimeScaling #FutureOfAI #EnterpriseAI