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Latent Distance Guided Alignment Training for Large Language Models

Ensuring alignment with human preferences is a crucial characteristic of large language models (LLMs). Presently, the primary alignment methods, RLHF and DPO, require extensive human annotation, which is expensive despite their efficacy.

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Cite this as

Haotian Luo (2024). Dataset: Latent Distance Guided Alignment Training for Large Language Models. https://doi.org/10.57702/8jb217g1

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Additional Info

Field	Value
Created	December 16, 2024
Last update	December 16, 2024
Defined In	https://doi.org/10.48550/arXiv.2404.06390
Author	Haotian Luo
Homepage	https://arxiv.org/abs/2309.00267