📄 arXiv 论文速递

💡 量子图上的非局部微分方程数值求解极具挑战，该框架首次将PINN扩展至该场景，为复杂网络物理系统建模提供新工具，具有重要理论价值。

We propose QGPINNs, a physics-informed neural network framework developed in PyTorch for the numerical solution of nonlocal differential equations on quantum graphs. The framework …

Tendon-driven hands are anthropomorphic, and moving the actuators off the joints is what makes a hand of this capability affordable to build. Two effects produce that saving. Routi…

💡 合成数据增强推理时易引入偏差，该研究提出尺寸-权重前沿方法，平衡真实与合成数据贡献，提升稀缺数据场景下的统计推断可靠性，实用性强。

Synthetic data can improve statistical inference when real data are scarce, but naively treating synthetic samples as real data can introduce bias and lead to unreliable inference.…

We study the mixing time of weighted Dikin walks for sampling from exponential distributions on polytopes and truncated positive-semidefinite (PSD) cones. Our first result gives a …

💡 针对各向异性高斯数据下的核岭回归，推导出精确渐近特性，揭示输入协方差幂律衰减对泛化误差的影响，为高维核方法设计提供理论指导。

We study kernel ridge regression under anisotropic Gaussian data, where the input covariance decays as a power law with exponent $α\geq 0$ for polynomial inner-product kernels. We …

Neural-network optimization in 2025-2026 is no longer well described as a succession of new Adam variants. The design space has expanded from coordinates to matrices and layers, fr…

Modern agent systems assemble capabilities at runtime, and this dynamic composition has recently received a complete formal treat ment in the spatiotemporal-composability calculus,…

As a precursor to high-dimensional biomedical data modeling, reliable feature selection can reduce computational expense, improve modeling performance, and yield simpler, more inte…

💡 将视频生成模型用于几何估计，突破传统图像扩散模型限制，利用时序信息提升深度与法向预测精度，为生成式几何理解开辟新方向。

Recent generative approaches to geometry estimation adapt pretrained image diffusion models and treat the task as image-conditioned generation. Leveraging off-the-shelf image diffu…

💡 多任务模型合并常因表示冲突而性能退化，该工作提出解码器感知的表示微调方法，有效提升合并后模型的多任务能力，对LLM高效部署意义重大。

Model merging combines multiple task-specific fine-tuned LLMs into a single multi-task model without additional training. However, merged models are known to suffer from representa…

A code world model accepted by a sampling gate can be exactly right on everything the gate can see and arbitrarily wrong beyond it. We characterize what a certified model can know,…

Recent advances in generative AI allow users to create 3D models from text or images. However, these models prioritize visual plausibility over geometric accuracy, often generating…