Hinted Scaling Laws 用提示辅助小模型预测大模型难题表现

"Hinted Scaling Laws"

Scaling laws can predict how LLMs improve with scale, how do you predict a larger model's performance on difficult benchmarks when all the smaller models score nearly zero?

This paper introduces Hinted Scaling Laws, which gives smaller models varying amounts of help, such as partial solutions, to reveal how their accuracy improves. Researchers then use these patterns to predict larger models' performance without hints.

Across GSM8K, AIME, and HLE, this reduces median forecasting error from 21 to 4.3%, making predictions of future model capabilities much more accurate.

https://www.alphaxiv.org/abs/2611.02270