To address the challenge, consistency models have been proposed to facilitate fast inference, albeit at the cost of sample quality.

Electronic health record (EHR) data has emerged as a valuable resource for analyzing patient health status.

Current studies on adversarial robustness mainly focus on aggregating local robustness results from a set of data samples to evaluate and rank different models.

Llama [Touvron et al., 2023] have become immensely popular due to their excellent performance

Large language models (LLMs) have recently demonstrated great success in generating and understanding natural language. While they have also shown potential beyond the domain of natural language, it remains an open question as to what extent and in which way these LLMs can plan.

Specifically, instead of directly measuring the divergence with paired images, we train a reward model with the dataset we construct, consisting of nearly 51,000 images annotated with human preferences.