AINeutralarXiv – CS AI · Apr 76/10
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Automatically Generating Hard Math Problems from Hypothesis-Driven Error Analysis
Researchers have developed a new automated pipeline that generates challenging math problems by first identifying specific mathematical concepts where LLMs struggle, then creating targeted problems to test these weaknesses. The method successfully reduced a leading LLM's accuracy from 77% to 45%, demonstrating its effectiveness at creating more rigorous benchmarks.
🧠 Llama