4 papers
MiniOpt: Reasoning to Model and Solve General Optimization Problems with Limited Resources
Ke Zhao, Zixiang Di, Hong Qian +9
Achieving strong optimization generalization across diverse optimization problems while requiring limited training resources remains a challenging problem for optimization-oriented…
VersaTune: An Efficient Data Composition Framework for Training Multi-Capability LLMs
Keer Lu, Keshi Zhao, Zhuoran Zhang +8
As demonstrated by the proprietary Large Language Models (LLMs) such as GPT and Claude series, LLMs have the potential to achieve remarkable proficiency across a wide range of doma…
DataSculpt: Crafting Data Landscapes for Long-Context LLMs through Multi-Objective Partitioning
Keer Lu, Xiaonan Nie, Zheng Liang +8
In recent years, Large Language Models (LLMs) have demonstrated significant improvements across a variety of tasks, one of which is the long-context capability. The key to improvin…
Data Proportion Detection for Optimized Data Management for Large Language Models
Hao Liang, Keshi Zhao, Yajie Yang +4
Large language models (LLMs) have demonstrated exceptional performance across a wide range of tasks and domains, with data preparation playing a critical role in achieving these re…