Summary
Generative large language models (LLMs) and generative diffusion models (GDMs) have become known for generating data that can have an astounding resemblance to human-generated content. Yet, the content generated by these models can introduce serious risks in specific applications. These models are known to replicate biases of their training data, produce unsafe outputs, and generate content that is misleading, false, and reprehensible. This project tackles these challenges within the general framework of alignment. Large pretrained models for image and language generation are available in the
