2 papers
cs.CL2025
AIDE: Attribute-Guided MultI-Hop Data Expansion for Data Scarcity in Task-Specific Fine-tuning
Jiayu Li, Xuan Zhu, Fang Liu +1
Fine-tuning large language models (LLMs) for specific tasks requires diverse, high-quality training data. However, obtaining sufficient relevant data remains a significant challeng…
cs.LG2024
Towards Improved Preference Optimization Pipeline: from Data Generation to Budget-Controlled Regularization
Zhuotong Chen, Fang Liu, Jennifer Zhu +2
Direct Preference Optimization (DPO) and its variants have become the de facto standards for aligning large language models (LLMs) with human preferences or specific goals. However…