Shijie Ma

VideoRover unifies video reasoning and external knowledge retrieval, achieving competitive performance with fewer resources than larger models.

Continual learning methods for Video-LLMs face a fundamental trade-off: mitigating catastrophic forgetting often comes at the cost of generalization or prohibitive computational overhead.

Context-augmented RL lets smaller MLLMs punch *way* above their weight, rivaling much larger models on reasoning tasks while dodging reward hacking.