Papers by Jixiang Hong

1 papers
CycleAlign: Iterative Distillation from Black-box LLM to White-box Models for Better Human Alignment (2024.findings-acl)

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Challenge: Existing language models that generate harmful responses are constrained by their inherent capability.
Approach: They propose to align large language models with human preferences from AI feedback.
Outcome: The proposed framework improves the alignment of large language models with human preferences from AI feedback.

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