2 citations · 2 across the 2 of their papers we have counts for
3 papers
cs.CL2025
ClusterUCB: Efficient Gradient-Based Data Selection for Targeted Fine-Tuning of LLMs
Zige Wang, Qi Zhu, Fei Mi +3
Gradient-based data influence approximation has been leveraged to select useful data samples in the supervised fine-tuning of large language models. However, the computation of gra…
cs.CL2023
Data Management For Training Large Language Models: A Survey
Zige Wang, Wanjun Zhong, Yufei Wang +6
Data plays a fundamental role in training Large Language Models (LLMs). Efficient data management, particularly in formulating a well-suited training dataset, is significant for en…
cs.LG2023★ 2 cited
SODA: Robust Training of Test-Time Data Adaptors
Zige Wang, Yonggang Zhang, Zhen Fang +3
Adapting models deployed to test distributions can mitigate the performance degradation caused by distribution shifts. However, privacy concerns may render model parameters inacces…