重新思考高分辨率多模态大模型中的Zoom-IN方法，提出Hierarchical Decoupling框架，显著提升视觉理解性能。
arXiv:2510.00054v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have made significant strides in visual understanding tas…
将语义解耦与LLM推理、扩散生成融合，实现通用图像编码新范式。
arXiv:2412.18158v2 Announce Type: replace Abstract: Learned image compression methods have shown impressive performance but are often highly specializ…
将工具调用与执行解耦，提出隐式层次化GRPO框架，显著提升数学推理中的工具集成效率与泛化能力。
arXiv:2605.18500v1 Announce Type: new Abstract: Large language models (LLMs) have increasingly leveraged tool invocation to enhance their reasoning ca…
自回归序列的矩阵解耦集中不等式，为稀疏长上下文奖励提供无维度保证，理论创新突破。
arXiv:2605.06017v2 Announce Type: replace Abstract: Sequence-level evaluations in autoregressive Large Language Models (LLMs) rely on highly dependent…
提出通过模型合并解耦数据混合搜索与训练，高效扩展LLM预训练的数据配比策略。
arXiv:2602.00747v2 Announce Type: replace-cross Abstract: Determining an effective data mixture is a key factor in Large Language Model (LLM) pre-trai…
DiLA将潜在动作解耦为几何与纹理流，实现高保真视频预测，突破LAMs的抽象-保真权衡。
arXiv:2605.15725v1 Announce Type: cross Abstract: Latent Action Models (LAMs) enable the learning of world models from unlabeled video by inferring ab…
自监督双轨框架首次解耦结构与内容，精准评估LLM在Web系统中的表现。
arXiv:2601.19923v2 Announce Type: replace-cross Abstract: As Large Language Models (LLMs) evolve into the core of Web-based autonomous agents and comp…
一篇揭示LLM金融治理中“治理-任务解耦”的突破性论文。作者提出机械执行四原语，将合规决策从模型视角剥离，使任务准确率从0.43飙升至0.88，同时大幅提升可审计性——治理质量不再随任务性能崩溃，从根本上重塑了可信AI治理范式。
arXiv:2605.14744v1 Announce Type: cross Abstract: Large language models in regulated financial workflows are governed by natural-language policies tha…