12 citations · 22 across the 3 of their papers we have counts for
3 papers
cs.CL2024★ 2 cited
Advancing Translation Preference Modeling with RLHF: A Step Towards Cost-Effective Solution
Nuo Xu, Jun Zhao, Can Zu +9
Faithfulness, expressiveness, and elegance is the constant pursuit in machine translation. However, traditional metrics like \textit{BLEU} do not strictly align with human preferen…
cs.CL2024★ 12 cited
LLM-DA: Data Augmentation via Large Language Models for Few-Shot Named Entity Recognition
Junjie Ye, Nuo Xu, Yikun Wang +4
Despite the impressive capabilities of large language models (LLMs), their performance on information extraction tasks is still not entirely satisfactory. However, their remarkable…
cs.AI2024★ 8 cited
Secrets of RLHF in Large Language Models Part II: Reward Modeling
Binghai Wang, Rui Zheng, Lu Chen +24
Reinforcement Learning from Human Feedback (RLHF) has become a crucial technology for aligning language models with human values and intentions, enabling models to produce more hel…