Large vision language models (LVLMs) integrate large language models (LLMs) with pre-
trained vision encoders, thereby activating the perception capability of the model to …

Automated alignment develops alignment systems with minimal human intervention. The
key to automated alignment lies in providing learnable and accurate preference signals for …

The rapid advancement of language models (LMs) necessitates robust alignment with
diverse user values. However, current preference optimization approaches often fail to …

Alignment is the most critical step in building large language models (LLMs) that meet
human needs. With the rapid development of LLMs gradually surpassing human …

Aligning pretrained language models (LMs) is a complex and resource-intensive process,
often requiring access to large amounts of ground-truth preference data and substantial …

Aligning pretrained language models (LMs) to handle a new safety scenario is normally
difficult and expensive, often requiring access to large amounts of ground-truth preference …

Reinforcement Learning from Human Feedback (RLHF) has greatly improved the
performance of modern Large Language Models (LLMs). The RLHF process is resource …