Existing methods like ensemble still struggle to aggregate these models with the desired higher-order communications. In this work, we propose Cola, a novel paradigm that coordinates multiple VLMs for visual reasoning.

In such cases, re-training the model from scratch could be time-consuming.

To address these challenges, we propose the instance-level adaptive propulsion of external knowledge (IAPEK), where we only conduct the retrieval when necessary.

Training offline RL models using visual inputs poses two significant challenges, i.e.,