Papers by Saeed Khaki

1 papers
RS-DPO: A Hybrid Rejection Sampling and Direct Preference Optimization Method for Alignment of Large Language Models (2024.findings-naacl)

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Challenge: Reinforcement learning with human feedback (RLHF) is widely employed to align large language models with user intent.
Approach: They propose to combine rejection sampling and direct preference optimization to improve alignment with user intent by identifying pairs of contrastive samples from human annotator and alternative LLMs.
Outcome: The proposed method outperforms existing methods including RS, PPO, and DPO in a limited resource environment.

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