VideoRFT

🎥 VideoRFT: Incentivizing Video Reasoning Capability in MLLMs via Reinforced Fine-Tuning Paper Code CoT Dataset (on Hugging Face) RL Dataset (on Hugging Face) Models (on Hugging Face) Abstract Reinforcement fine-tuning (RFT) has shown great promise in achieving humanlevel reasoning capabilities of Large Language Models (LLMs), and has recently been extended to MLLMs. Nevertheless, reasoning about videos, which is a fundamental aspect of human intelligence… See the full description on the dataset page:

Source: Hugging Face Hub (QiWang98/VideoRFT-Data). Metadata imported from the dataset’s Hub tags.