提出原则性样本选择方法提升LLM退火效率，向高质量模型训练迈进。
arXiv:2605.31175v1 Announce Type: new Abstract: The annealing phase is a pivotal convergence stage in LLM pre-training that ultimately determines fina…
提出Leveraging Diversity of Least方法，通过平衡不确定性与多样性优化主动学习样本选择，提升模型训练效率
arXiv:2605.22169v1 Announce Type: new Abstract: Deep learning models, including Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs), h…
揭示视觉指令调优中样本信息性的关键作用，COMPACT方法用少量高信息样本高效微调多模态大模型
arXiv:2504.21850v3 Announce Type: replace Abstract: Visual instruction tuning (VIT) datasets have grown rapidly in scale, yet the informativeness of i…