Unverified50% confidenceFactExact time
In the field of automated model optimization, there are already some comparable real works, such as using large models to search for better prompts, data recipes or training hyperparameters (e.g., automatic prompt engineering, attempts to combine neural architecture search with large models).
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11/3/2026
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UnverifiedWhat existing automated model optimization works have in common is that the large model outputs suggestions or configurations, and it is still the training pipeline that actually changes the model parameters.80% similarVerifiedCurrent large model evaluation procedures often provide models with complete questions and conditions, and conduct targeted training on specific question banks, making high scores easy to achieve.75% similarUnverifiedFormalized data can serve as high-quality training corpus for AI proof systems, improving machine reasoning capabilities.75% similarUnverifiedThe large model algorithm research direction focuses on foundational research within enterprises, including writing operators, optimizing the large model itself, and optimizing training and inference processes.75% similarUnverifiedPaths for improving model intelligence include increasing training and inference computation, optimizing reasoning architectures, and strengthening chain-of-thought training.74% similar
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