CLIP

RAFT: Reward rAnked FineTuning - A New Approach to Generative Model Alignment

Summary This post is an explanation of this paper:RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment. Generative foundation models, such as Large Language Models (LLMs) and diffusion models, have revolutionized AI by achieving human-like content generation. However, they often suffer from Biases – Models can learn and reinforce societal biases present in the training data (e.g., gender, racial, or cultural stereotypes). Ethical Concerns – AI-generated content can be misused for misinformation, deepfakes, or spreading harmful narratives.