Unverified50% confidenceSolutionExact time
Selecting the already-trained model whose parameters are closest to a specific trade-off point to approximate that point is a method with some effectiveness.
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Long-term
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9/24/2026
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UnverifiedMerging the parameters of multiple trained models to generate new trade-off combinations has been shown to be helpful.79% similarUnverifiedDuring the pretraining phase, the model's objective function is typically to maximize the log-likelihood of the next token and does not include signals for refusing to answer.78% similarUnverifiedCurrent 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.78% similarUnverifiedThe core idea of the test-time compute paradigm is to shift resources from the training phase to the answer generation process, trading more inference compute for higher-quality output.76% similar
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