Yongnan Jin

DRBO: Mitigating the Bottleneck Effect via Dynamic Reward Balancing in Multi-reward LLM Optimization

In the current landscape of large language models (LLMs), many evaluation metrics have been developed and used as rewards during training to improve specific metrics. However, balancing these metrics and dynamically adjusting reward weights remains challenging, as current approaches often fail to en