(3) [Paper Review] Fine-Tuning Large Vision-Language Models as Decision-Making Agents via Reinforcement Learning: Embodied AI
Today, I will review a new paper that was released yesterday. This research comes from Sergey Levineโs team, a prominent figure in the AI and RL domains. They propose fine-tuning Vision-Language Models (VLM) with Reinforcement Learning (RL) to enhance performance in optimal decision-making tasks within multi-step interactive environments. The paper presents a simple approach that outperforms both GPT-4 and Gemini. This research is similar to my own ideas for solving challenges in embodied AI. Therefore, I will review this paper and organize its key concepts.