adaptive-mixing

Introduces AdaWeather, an adaptive framework that combines multiple probabilistic weather forecasts using machine learning and mixture of experts, achieving logarithmic regret compared to the best static mixture of experts and showing empirical improvements in temperature forecasting.

The paper proposes GAC, a noise-aware adaptive mixing controller for hybrid SFT-RL post-training of LLMs. It derives a closed-form mixing weight that balances gradient noise and SFT-RL disagreement, achieving consistent improvements across multiple benchmarks with minimal overhead.