I’m interested in building agents that learn representations from rich human knowledge, whether directly (e.g. from users) or through priors (e.g. from LMs). Currently, I’m thinking a lot about how to utilize pretrained models in conjunction with human feedback to interactively learn aligned representations/rewards.