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Abandoning arithmetic logic for string similarity allows LLMs to achieve unprecedented accuracy in deducing logical rules from binary strings.
Even the most advanced models fall short, with only 5.6% accuracy on new benchmarks, highlighting a critical gap in semantic understanding in code generation.
