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Tightening the bounds on hyperparameter tuning could revolutionize how we approach model optimization in machine learning.
LLMs struggle to generate correct COBOL code, but a simple compilation-guided repair loop can boost success rates by over 50%.
GPT-4o can't even compile COBOL, but COBOL-Coder, a new domain-adapted LLM, achieves a 74% compilation success rate, finally bringing modern AI to legacy mainframe systems.
