定义LLM提示复杂度的新概念，探究指令调优模型最短合理提示的边界。
arXiv:2607.06145v1 Announce Type: new Abstract: In this paper, we define the quantity of prompting complexity: for a fixed instruction-tuned language …
卢森堡语大模型指令调优数据集LuxIT正式开源，独创单语种子数据高效构建方案，为低资源语言NLP突破奠定基础。
arXiv:2510.24434v3 Announce Type: replace Abstract: The effectiveness of instruction-tuned Large Language Models (LLMs) is often limited in low-resour…
编辑单个神经元，就能修复大模型在长枚举任务中的重复循环崩溃？这项研究揭示了 Gemma 4 模型的深层问题与解法。
arXiv:2606.13705v1 Announce Type: cross Abstract: Yes. Can it cure doom loops? Probably not. The Gemma 4 instruction-tuned models share a reproducible…
通过抽象方法对齐视觉与语言，这篇论文提出了一种新颖的视觉指令调优框架。
arXiv:2606.03871v1 Announce Type: new Abstract: Visual instruction tuning effectively adapts a pre-trained Large Language Model (LLM) to process image…
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…