Data Management For Large Language Models: A Survey. - Zige Wang; Wanjun Zhong; Yufei Wang 005; Qi Zhu 011; Fei Mi; Baojun Wang; Lifeng Shang; Xin Jiang 002; Qun Liu 001 (CoRR, 2023)

Planning, Creation, Usage: Benchmarking LLMs for Comprehensive Tool Utilization in Real-World Complex Scenarios. - Shijue Huang; Wanjun Zhong; Jianqiao Lu; Qi Zhu 011; Jiahui Gao; Weiwen Liu; Yutai Hou; Xingshan Zeng; Yasheng Wang; Lifeng Shang; Xin Jiang 002; Ruifeng Xu 001; et al. (ACL (Findings), 2024)

YODA: Teacher-Student Progressive Learning for Language Models. - Jianqiao Lu; Wanjun Zhong; Yufei Wang 005; Zhijiang Guo; Qi Zhu 011; Wenyong Huang; Yanlin Wang 001; Fei Mi; Baojun Wang; Yasheng Wang; Lifeng Shang; Xin Jiang 002; et al. (CoRR, 2024)

Self-Error-Instruct: Generalizing from Errors for LLMs Mathematical Reasoning. - Erxin Yu; Jing Li 049; Ming Liao; Qi Zhu 011; Boyang Xue; Minghui Xu; Baojun Wang; Lanqing Hong; Fei Mi; Lifeng Shang (ACL (1), 2025)

Mutual Reinforcement of LLM Dialogue Synthesis and Summarization Capabilities for Few-Shot Dialogue Summarization. - Yen-Ju Lu; Ting-Yao Hu; Hema Swetha Koppula; Hadi Pouransari; Jen-Hao Rick Chang; Yin Xia; Xiang Kong; Qi Zhu 011; Simon Wang; Oncel Tuzel; Raviteja Vemulapalli (NAACL (Findings), 2025)

Dynamic data selection with normalized gradient-based influence approximation for targeted fine-tuning of LLMs. - Zige Wang; Qi Zhu 011; Fei Mi; Yasheng Wang; Haotian Wang; Lifeng Shang (Knowl. Based Syst., 2025)

How Should We Enhance the Safety of Large Reasoning Models: An Empirical Study. - Zhexin Zhang; Xian Qi Loye; Victor Shea-Jay Huang; Junxiao Yang; Qi Zhu 011; Shiyao Cui; Fei Mi; Lifeng Shang; Yingkang Wang; Hongning Wang; Minlie Huang (CoRR, 2025)

ClusterUCB: Efficient Gradient-Based Data Selection for Targeted Fine-Tuning of LLMs. - Zige Wang; Qi Zhu 011; Fei Mi; Minghui Xu; Ruochun Jin; Wenjing Yang (CoRR, 2025)