Large Language Models (LLMs) have recently demonstrated remarkable capabilities in
natural language processing tasks and beyond. This success of LLMs has led to a large …

Data annotation generally refers to the labeling or generating of raw data with relevant
information, which could be used for improving the efficacy of machine learning models. The …

Language is essentially a complex, intricate system of human expressions governed by
grammatical rules. It poses a significant challenge to develop capable AI algorithms for …

We present a comprehensive solution to learn and improve text-to-image models from
human preference feedback. To begin with, we build ImageReward---the first general …

Reinforcement learning from human feedback (RLHF) is an effective technique for aligning
large language models (LLMs) to human preferences, but gathering high-quality human …

Despite the stunning ability to generate high-quality images by recent text-to-image models,
current approaches often struggle to effectively compose objects with different attributes and …

Large language models (LLMs), exemplified by ChatGPT, have gained considerable
attention for their excellent natural language processing capabilities. Nonetheless, these …

Reinforcement learning from human feedback (RLHF) is a technique for training AI systems
to align with human goals. RLHF has emerged as the central method used to finetune state …

Reinforcement Learning from Human Feedback (RLHF) facilitates the alignment of large
language models with human preferences, significantly enhancing the quality of interactions …

Large language models (LLMs), such as GPT-4, have shown remarkable performance in
natural language processing (NLP) tasks, including challenging mathematical reasoning …