Unverified50% confidenceFactExact time
The target score identity expresses the score function as a self-consistent relation between the current model prediction and the gradient of the unnormalized density, making it possible to construct a training objective without external training data.
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10/14/2026
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UnverifiedDuring 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.79% similarUnverifiedIn diffusion models, the score function is used to describe the log gradient of the data distribution and is trained via denoising score matching.77% similarUnverified分位数回归通过直接对目标变量的条件分位数建模（如同时训练 5%、50%、95% 分位点）来得到预测中位数和区间，不需要假设误差服从高斯分布，对长尾或非对称分布更稳健。77% similarUnverifiedA base model is the original version that has completed pre-training on large-scale data but has not been fine-tuned for a specific task, retaining the most complete parameter space and generalization potential.75% similarUnverifiedThe fundamental issue of cross-task calibration is that the model's probability output is learned on a specific training distribution; when the input distribution changes, the reliability of the probabilities drifts but the model cannot perceive it.74% similar
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