most citedICDPO: Effectively Borrowing Alignment Capability of Others via In-context Direct Preference Optimization

1 citations · 2 across the 3 of their papers we have counts for

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cs.CL2024★ 1 cited

Towards a Unified View of Preference Learning for Large Language Models: A Survey

Bofei Gao, Feifan Song, Yibo Miao +22

Large Language Models (LLMs) exhibit remarkably powerful capabilities. One of the crucial factors to achieve success is aligning the LLM's output with human preferences. This align…

cs.CL2024

Utilizing Local Hierarchy with Adversarial Training for Hierarchical Text Classification

Zihan Wang, Peiyi Wang, Houfeng Wang

Hierarchical text classification (HTC) is a challenging subtask of multi-label classification due to its complex taxonomic structure. Nearly all recent HTC works focus on how the l…

cs.CL2024★ 1 cited

ICDPO: Effectively Borrowing Alignment Capability of Others via In-context Direct Preference Optimization

Feifan Song, Yuxuan Fan, Xin Zhang +2

Large Language Models (LLMs) rely on Human Preference Alignment (HPA) to ensure the generation of safe content. Due to the heavy cost associated with fine-tuning, fine-tuning-free…