Reinforcement learning (RL) shows promise for task-specific agents but suffers from high sample complexity, limiting practical applications. To address these challenges, we introduce LVLM to Policy ...

In this paper, we propose a sample-level multimodal self-paced learning strategy (SMSL). It first assesses the degree of modality imbalance in each sample and progressively learns the weaker ...