LD Align

LD Align, or Latent Distance Guided Alignment, focuses on improving the alignment of large language models (LLMs) with human preferences without relying on extensive human annotation. Current research emphasizes techniques like optimal transport and latent space analysis to guide the alignment process, often within frameworks employing mixture-of-experts architectures or teacher-student models for efficient training. This research area is significant because it addresses the high cost and scalability challenges associated with existing LLM alignment methods, potentially leading to more efficient and ethically sound AI systems across various applications.