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课程调度中的相变阈值

使用渗流风格的阈值估计来决定课程何时应切换模式，而不是依赖固定的时期截止。

用于医学图像合成的扩散形变先验

将临床上有意义的图像合成视为变形和不确定性上的传输，而不仅仅是强度翻译。

变分能量塑形用于规划网络

将神经规划模块视为能量塑造系统，其更新应保持在可行值景观之内。

面向血管重建的拓扑感知距离场

利用距离场监督作为结构化重建任务中局部几何与全局网络有效性之间的桥梁。

不确定性校准置信图用于鲁棒感知

将置信度作为控制推理的一等字段，而不仅仅是预测后的诊断叠加层。

全球研究帖子的翻译流程

同构搜索的特征排序

非平衡轨迹上的熵产生局部化

Entropy production is a universal measure of irreversibility and energy dissipation in physical, chemical, and biological systems operating far from equilibrium.

关于小型图神经网络在求解线性规划中的能力

Graph neural networks (GNNs) have recently emerged as powerful tools for addressing complex optimization problems.

电可切换连续相位液晶菲涅尔波带片

We present the design, fabrication, and characterization of continuous phase Fresnel zone plates (FZPs) using two-photon polymerization direct laser writing in a polymerizable nematic liquid crystal (LC) confined...

跨域医学组织学自适应染色归一化

Deep learning advances have revolutionized automated digital pathology analysis.

Ba掺杂 KTaO3 中大声子拖曳热电势极性反转

This study reports the observation of phonon-drag thermopower polarity reversal in Ba-doped KTaO3 thin films, mediated by electron-phonon Umklapp scattering.

非球形杂质对非晶态固体延性-脆性转变临界点的影响

Enhancing the mechanical strength and stability of amorphous solids is crucial for material design, with microalloying being a common yet poorly understood method.

植被-水分模型双饱和转化项动力学行为分析

In this paper, we propose a vegetation-water system incorporating double saturation transformation terms, which more vividly depicts the mutual influence and transformation relationship between vegetation and water.

Rotated Runtime Smooth: 训练无关的激活平滑器，用于精确的 INT4 推理

Large language models have demonstrated promising capabilities upon scaling up parameters.

联邦模型异构的嵌套表示学习

Model heterogeneous federated learning (MHeteroFL) enables FL clients to collaboratively train models with heterogeneous structures in a distributed fashion.

多维频率比特纠缠量子密钥分发网络

Quantum networks enhance quantum communication schemes and link multiple users over large areas.

面向自然对话的具身智能大语言模型：融合韵律感知

Recent work shows promising results in expanding the capabilities of large language models (LLM) to directly understand and synthesize speech.

相互作用量子网络超越对称性约束的集体净化

Following any quantum information processing protocol, it is essential to reset a mixed state of a many-body interacting spin-network to the computational-zero pure state.

低能自旋波在超导电子掺杂铜氧化物中的涌现

In order to fully utilize the technological potential of unconventional superconductors, an enhanced understanding of the superconducting mechanism is necessary.

RFWave：用于音频波形重建的多频段整流流

Recent advancements in generative modeling have significantly enhanced the reconstruction of audio waveforms from various representations.

SrRuO3薄膜中的各向异性磁阻与磁场可调的Weyl节点

Weyl semimetals are a unique class of topological materials, possessing Fermi-arc surface states and exhibiting the chiral anomaly effect.

嵌入轨迹用于数学推理中的分布外检测

Real-world data deviating from the independent and identically distributed (\textit{i.i.d.}) assumption of in-distribution training data poses security threats to deep networks, thus advancing out-of-distribution...

多功能光纤诊疗探针用于闭环肿瘤光热治疗

The combination of optical fiber and phototheranostic agents has emerged as a promising strategy to address the challenges of limited light penetration depth and systemic toxicity of nanomaterials.

Legendre-Laguerre-基混合多项式的扩展形式及其通过分数算子方法的特征

This study presents an extensive generalization of Legendre–Laguerre polynomials along with their Appell-type counterparts.

MTSAM：面向分割任意模型的任务微调

The Segment Anything Model (SAM), with its remarkable zero-shot capability, has the potential to be a foundation model for multi-task learning.

Magic Tricycles: 使用有限块长量子LDPC码实现高效魔态生成

The preparation of high-fidelity non-Clifford (magic) states is an essential subroutine for universal quantum computation but imposes substantial space-time overhead.

宁夏地区布鲁氏菌病差异化最优控制策略：来自双区域动力学模型的洞见

As a high-incidence region of brucellosis in China, the incidence pattern of brucellosis in Ningxia shows a significant spatial-temporal heterogeneity, thus, it is of significance to allocate the differentiated...

QKAN：量子Kolmogorov-Arnold网络及其在机器学习和多变量状态制备中的应用

We introduce quantum Kolmogorov-Arnold networks (QKAN), a quantum algorithmic framework inspired by the recently proposed Kolmogorov-Arnold Networks (KAN).

利用图强化学习加速原子精细结构测定

Atomic data determined by analysis of observed atomic spectra are essential for plasma diagnostics.

SARS-CoV-2感染引起的免疫衰退的丰富动力学与数据分析

The global pandemic of SARS-CoV-2 has constituted a serious threat to public health.

泛化界与无毒标签后门攻击的新算法

The generalization bound is a crucial theoretical tool for assessing the generalizability of learning methods and there exist vast literatures on generalizability of normal learning, adversarial learning, and data...

EuCd$_2$P$_2$ 反铁磁 CMR 系统中的鲁棒磁极化子渗流

The interplay between magnetism and charge transport is central to understanding colossal magnetoresistance (CMR), a phenomenon well studied in ferromagnets.

Layered KIK quantum error mitigation for dynamic circuits

Layered KIK quantum error mitigation for dynamic circuits

气球机制：液滴弹性实现完全回弹

New research shows tuning liquid & surface properties prevents splashing at high speeds.

能量引导的连续熵中心估计（Energy-Guided Continuous Entropic Barycenter Estimation）用于一般成本函数

This paper introduces a new, simpler way to average probability distributions that keeps their shape, with guaranteed quality and real-world applications.

非局域性、可积性与贝尔算符谱中的量子混沌

New research reveals maximal entanglement in 3-state systems leads to predictable, non-chaotic behavior.

延迟扩散型尼科尔森麻蝇方程的全局指数稳定性分析

A modified Nicholson’s blowflies equation accompanying distinct time-varying delays is established in this paper.

量化口蹄疫病毒的气溶胶传播距离

Foot-and-mouth disease (FMD) is an acute, febrile, and highly contagious animal infectious disease that can be transmitted through multiple routes.

高速值迭代网络 (Highway Value Iteration Networks)

Value iteration networks (VINs) enable end-to-end learning for planning tasks by employing a differentiable "planning module" that approximates the value iteration algorithm.

非阿贝尔拓扑序中的稳定器码之间的非克利福德门

We propose protocols to implement non-Clifford logical gates between stabilizer codes by entangling into a non-Abelian topological order as an intermediate step.

洞悉表面之下：从彩色眼底照片预测黄斑水肿的视网膜厚度图，助力DME管理

New model turns basic eye scans into detailed maps, boosting DME diagnosis in low-resource areas.

扩散模型在视觉、语言和控制中的非渐进式推理摊销

Diffusion models have emerged as effective distribution estimators in vision, language, and reinforcement learning, but their use as priors in downstream tasks poses an intractable posterior inference problem.

D3M：用于脑肿瘤增强核磁共振成像合成的变形驱动扩散模型

Contrast-enhanced magnetic resonance images (CEMRIs) provide valuable information for brain tumor diagnosis and treatment planning.

RuBr3：Kitaev模型候选材料的磁激发

New study reveals RuBr3's magnetic interactions push it from ideal spin liquid state, offering clues for quantum computing materials.

谐振耦合微腔中的高能效超宽带孤子微梳

The drive to miniaturize optical frequency combs for practical deployment has spotlighted microresonator solitons as a promising chip-scale candidate.

连续变量量子网络中的负熵渗流

New theory reveals unique "mixed-order" entanglement transitions, paving way for chip-scale quantum tech.

通过输入态设计增强变分量子算法的可达性

Design smarter inputs to unlock deeper insights & boost accuracy in quantum algorithms.

Fluxonium作为控制量子比特以实现玻色子量子信息

Bosonic codes in superconducting resonators are a hardware-efficient avenue for quantum error correction and benefit from the inherent bias toward relaxation errors provided by long-lived cavities compared to typical...

实验性安全多方计算基于量子不可见传输和比特承诺

Secure multiparty computation enables collaborative computations across multiple users while preserving individual privacy, which has a wide range of applications in finance, machine learning and healthcare.

合约性幺正与经典阴影层析成像

Here's a breakdown of the abstract, designed for a zero-base reader:

关于 Hausdorff 内容极大算子和 Riesz 势对于不可测函数的研究

We introduce Riesz potentials for Lebesgue non-measurable functions by taking the integrals in the sense of Choquet with respect to Hausdorff content and prove boundedness results for these operators.

变界变分空间中Mellin卷积型非线性积分算子的逼近

In this paper, we investigate approximation properties using a family of Mellin convolution-type integral operators within the framework of variable bounded variation spaces with the help of summability methods.

DentEval：通过LLM Agent实现免微调的专家对齐评估在牙科教育中的应用

Large language models (LLMs) have demonstrated considerable potential in automating assignment scoring within higher education, providing efficient and consistent evaluations.

高阶非线性微分方程在正则情形下的振荡行为

In this paper, we study the oscillation of a class of higher-order neutral nonlinear differential equations.

通过热浴算法冷却改进量子机器学习

This work introduces an approach rooted in quantum thermodynamics to enhance sampling efficiency in quantum machine learning (QML).

VesselSDF：用于血管网络重建的距离场先验

VesselSDF uses a new "distance field" approach to perfectly map blood vessels from sparse CT scans, overcoming past limitations.

混合动机环境下的分层对手建模与规划实现高效适应

Despite the recent successes of multi-agent reinforcement learning (MARL) algorithms, efficiently adapting to co-players in mixed-motive environments remains a significant challenge.

具有无标签分割和无训练图像翻译的头皮诊断系统

ScalpVision tackles data challenges for better, cheaper, and more accessible skin care.

FluoroSAM：一种可语言提示的、用于灵活X射线图像分割的基础模型

Language promptable X-ray image segmentation would enable greater flexibility for human-in-the-loop workflows in diagnostic and interventional precision medicine.

PhoCoLens：无透镜成像中的照片级真实感与一致性重建

New AI reconstructs stunning images from simple sensors, overcoming past limitations.

动态停滞在活性向列湍流中

Active fluids display spontaneous turbulentlike flows known as active turbulence.

对组合多臂老虎机（CMAB）的对抗性攻击

New research reveals how to identify and exploit vulnerabilities in "reward poisoning" attacks on a type of AI decision-making system, showing attacks are harder than previously thought.

基于沃尔什-哈达玛变换的线性向量符号架构

Vector Symbolic Architectures (VSAs) are one approach to developing Neuro-symbolic AI, where two vectors in are 'bound' together to produce a new vector in the same space.

虚假特征的记忆机制：随机特征与NTK特征的精确分析

This paper offers a theoretical explanation for why AI models memorize irrelevant data, revealing how model stability and feature alignment play key roles.

超越阴影：从稀疏标注中学习受物理启发的超声置信度图

This paper introduces a novel user-centered approach for generating confidence maps in ultrasound imaging.

向量量化驱动的主动学习，用于跨模态辅助的高效多模态医学图像分割

Multi-modal medical image segmentation leverages complementary information across different modalities to enhance diagnostic accuracy, but faces two critical challenges: the requirement for extensive paired...

TAPNext：将任意点追踪（TAP）视为下一个Token预测

The problem of "correspondence" has been a foundational challenge in computer vision for decades.

milliMamba：基于双毫米波雷达和多帧Mamba融合的视网膜感知人体姿态估计

The problem of Human Pose Estimation (HPE) using millimeter-wave (mmWave) radar signals emerged primarily as a response to the limitations of traditional camera-based (RGB) systems.

生成视频传播

The problem of generative video propagation, as addressed in this paper, is rooted in the broader field of computer vision, specifically within the domain of video generation and editing.

INST-IT：通过显式视觉提示指令调优提升实例理解能力

The problem addressed in this paper precisely originates from the recent advancements and, paradoxically, the limitations of Large Multimodal Models (LMMs) in the field of artificial intelligence, specifically within...

All-in-one medical image-to-image translation

Unifies translation, offers semantic control, and works without fine-tuning.

Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow

Rectified Flow learns straight paths to efficiently generate and transfer data between distributions.

RedDino：用于红细胞分析的基础模型

RedDino analyzes red blood cell images with unprecedented accuracy, paving the way for faster disease diagnosis.

基于膝关节MR图像重构健康画像的患者特异性放射组学特征选择

New method combines interpretable "radiomic features" with AI-generated "healthy scans" for better, explainable medical image analysis.

MeDi: 用于缓解肿瘤分类偏差的元数据引导扩散模型

Deep learning models have made significant advances in histological prediction tasks in recent years.

用于TMR传感器MCG信号去噪的多层门控U-Net

New AI model dramatically cleans up heart signals from cheap sensors for better medical use.

基于层级部件的真实感三维血管生成模型

Advancements in 3D vision have increased the impact of blood vessel modeling on medical applications.

Prompt-DAS: 面向电子显微镜图像域自适应语义分割的标注高效型提示学习

Prompt-DAS adapts AI to segment tiny cell parts in electron microscope images, offering flexible, efficient, and interactive annotation.

基于弱监督动作识别的可解释性 ADHD 诊断框架

The clinical diagnosis of Attention Deficit Hyperactivity Disorder (ADHD) primarily relies on scale questionnaires, clinical interviews, and executive function tests, which face challenges including limited medical...

LiteTracker：利用时间因果关系实现高精度、低延迟的组织追踪

LiteTracker achieves lightning-fast, accurate endoscopic tissue tracking for real-time surgery.

用于少样本器官分割的正则化低秩自适应（Regularized Low-Rank Adaptation）

New method auto-adjusts rank for better segmentation, outperforming others in few-shot learning.

Hybrid Graph Mamba：解锁非欧几里得潜能以实现精准息肉分割

Colorectal polyp segmentation can assist doctors in screening colonoscopy images, which is crucial for the prevention of colorectal cancer.

SOO-Bench：离线黑盒优化稳定性评估基准

The problem of Offline Black-Box Optimization (BBO) emerged from the practical necessity of optimizing complex systems where direct, real-time evaluation of the objective function is either too dangerous,...

通过平坦损失平面上的集成学习实现可泛化 3D 人体姿态估计

The quest to understand human movement in three dimensions from simple two-dimensional images—like those from a standard smartphone camera—is a cornerstone of modern computer vision.

计算受限的数据选择 (Compute-Constrained Data Selection)

The field of large language models (LLMs) has seen explosive growth, leading to models with billions of parameters capable of remarkable feats in natural language understanding and generation.

单张图像测试时自适应的多视角协同训练

Test-time adaptation enables a trained model to adjust to a new domain during inference, making it particularly valuable in clinical settings where such on-the-fly adaptation is required.

CENet：用于医学图像分割的上下文增强网络

CENet boosts medical image segmentation by enhancing boundaries and preserving details across diverse image types.

基于几何潜在嵌入的时间序列图引导纵向数据生成

This paper introduces a new AI model that creates realistic "time-lapse" medical images from static scans, helping us understand how body parts grow and change.

多管电压vBMD测量：双分支频率平衡与非对称通道注意力

Phantom-less volumetric bone mineral density (vBMD) measurement using computed tomography (CT) presents a cost-effective alternative to conventional phantom-based approaches, yet faces accuracy challenges across...

残余后模式的脑连接特征精炼

New AI model RP-LGN captures subtle connectivity changes for better disease diagnosis, outperforming others with improved accuracy & noise handling.

单次主动学习用于血管分割

New AI learns from tiny, smart samples, saving time & resources for better disease insights.

基于增强人体解剖知识的超声图像解剖结构少样本检测

Deep learning-based models have significantly advanced clinical ultrasound tasks by detecting anatomical structures within vast ultrasound image datasets.

跨模态脑图谱Transformer：基于功能-结构连通性网络的大脑疾病诊断

Multi-modal brain networks represent the complex connectivity between different brain regions from both functional and structural perspectives, which is of great significance for brain disease diagnosis.

共形预测集的反事实解释

New counterfactual explanations make complex "prediction sets" from AI understandable by showing minimal changes that alter the AI's output.

基于检索的视觉上下文学习的术前术后MRI生成

New AI generates realistic post-op MRIs from pre-op scans, aiding brain tumor surgery.

基于雷达的医学交流手语识别成像

This paper introduces a privacy-preserving radar system for recognizing Italian Sign Language in medical settings, achieving high accuracy.

本地PDF队列测试

Physics-informed neural networks (PINN) have achieved notable success in solving partial differential equations (PDE), yet solving the Navier-Stokes equations (NSE) with complex boundary conditions remains a...

学习以提高识别过程中额外 b 喷注的匹配效率

To truly understand the significance of this paper, we have to travel back to the monumental discovery of the Higgs boson at the Large Hadron Collider (LHC) in 2012.

混合边界物理信息神经网络求解复杂边界的Navier-Stokes方程

Physics-informed neural networks (PINN) have achieved notable success in solving partial differential equations (PDE), yet solving the Navier-Stokes equations (NSE) with complex boundary conditions remains a...

小波驱动解耦与物理信息映射网络用于加速多参数磁共振成像

Multi-parametric magnetic resonance imaging (MRI) is an advanced MRI technique that can provide multiple quantitative maps simultaneously based on acquired multi-echo images.