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Johns Hopkins University(约翰斯·霍普金斯大学)

共收录 1184
2511.20081 2025-11-26 cs.CV

Blind Adaptive Local Denoising for CEST Imaging

盲适应性局部去噪用于CEST成像

Chu Chen, Aitor Artola, Yang Liu, Se Weon Park, Raymond H. Chan, Jean-Michel Morel, Kannie W. Y. Chan

机构 * Department of Mathematics(数学系) City University of Hong Kong(城市大学) Hong Kong Centre for Cerebro-cardiovascular Health Engineering(香港脑心血管健康工程中心) Department of Biomedical Engineering(生物医学工程系) Department of Operations and Risk Management(运营与风险管理系) School of Data Science, Lingnan University(岭南大学数据科学学院) Division of Industrial Data Science(工业数据科学系) Department of Radiology and Radiological Science(放射科与放射科学系) Johns Hopkins University School of Medicine(约翰霍普金斯大学医学院)

AI总结 本文提出了一种盲适应性局部去噪方法,用于改进CEST成像中的噪声处理,提高分子信号分离和癌症检测的准确性。

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2511.19675 2025-11-26 math.OC cs.RO cs.SY eess.SY

Anytime-Feasible First-Order Optimization via Safe Sequential QCQP

通过安全序列二次约束二次规划实现随时可行的一阶优化

Jiarui Wang, Mahyar Fazlyab

机构 * Department of Electrical and Computer Engineering, Johns Hopkins University(电气与计算机工程系,约翰霍普金斯大学)

AI总结 本文提出了一种保证每次迭代可行性的安全序列二次约束二次规划算法,通过自适应步长选择和主动集变种提升可扩展性,展现$O(1/t)$收敛速度并达到与二阶求解器相当的解质量。

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2511.19526 2025-11-26 cs.CV

Perceptual Taxonomy: Evaluating and Guiding Hierarchical Scene Reasoning in Vision-Language Models

感知分类:评估和引导视觉语言模型中的层次场景推理

Jonathan Lee, Xingrui Wang, Jiawei Peng, Luoxin Ye, Zehan Zheng, Tiezheng Zhang, Tao Wang, Wufei Ma, Siyi Chen, Yu-Cheng Chou, Prakhar Kaushik, Alan Yuille

机构 * Johns Hopkins University(约翰霍普金斯大学)

AI总结 本文提出感知分类基准测试,旨在评估和引导视觉语言模型在层次场景推理中的能力,揭示模型在属性驱动推理上的不足,并展示通过上下文示例提升性能的效果。

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2511.18382 2025-11-25 cs.CV

ViMix-14M: A Curated Multi-Source Video-Text Dataset with Long-Form, High-Quality Captions and Crawl-Free Access

ViMix-14M:一个经过精心整理的多源视频-文本数据集,具有长形式、高质量的描述和无爬虫访问

Timing Yang, Sucheng Ren, Alan Yuille, Feng Wang

机构 * Johns Hopkins University(约翰霍普金斯大学)

AI总结 ViMix-14M是一个经过精心整理的多源视频-文本数据集,提供无爬虫访问、高质量描述和长形式文本,用于提升视频生成和多模态任务的性能。

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2511.18380 2025-11-25 cs.CV

RNN as Linear Transformer: A Closer Investigation into Representational Potentials of Visual Mamba Models

RNN作为线性Transformer:对视觉Mamba模型表示潜力的深入探讨

Timing Yang, Guoyizhe Wei, Alan Yuille, Feng Wang

机构 * Johns Hopkins University(约翰霍普金斯大学)

AI总结 本文深入研究了视觉Mamba模型的表示潜力,揭示其与Softmax和线性注意力的关系,并通过定量评估证明其在长距离依赖建模中的能力,同时展示了其在ImageNet上的高性能表现。

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2511.17869 2025-11-25 cs.LG

The Horcrux: Mechanistically Interpretable Task Decomposition for Detecting and Mitigating Reward Hacking in Embodied AI Systems

霍克鲁斯:用于检测和缓解具身AI系统中奖励黑客行为的可解释任务分解

Subramanyam Sahoo, Jared Junkin

机构 * Berkeley AI Safety Initiative (BASIS) UC Berkeley(伯克利人工智能安全计划(BASIS)伯克利大学) Department of Electrical and Computer Engineering Johns Hopkins University(电气与计算机工程系约翰霍普金斯大学)

AI总结 本研究提出MITD方法,通过可解释性任务分解有效检测和缓解具身AI系统中的奖励黑客行为,实验表明分解深度可显著降低奖励黑客频率。

Comments Accepted to the NeurIPS (Mexico City) 2025 Workshop on Embodied and Safe-Assured Robotic Systems (E-SARS). Thanks to Aman Chadha

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2505.21697 2025-11-25 cs.CV

Learning to Upscale 3D Segmentations in Neuroimaging

在神经影像中学习提升3D分割

Xiaoling Hu, Peirong Liu, Dina Zemlyanker, Jonathan Williams Ramirez, Oula Puonti, Juan Eugenio Iglesias

机构 * Massachusetts General Hospital and Harvard Medical School(麻省总医院和哈佛医学院) Department of ECE, Johns Hopkins University(约翰霍普金斯大学电子工程系) Danish Research Centre for Magnetic Resonance, Copenhagen University Hospital(丹麦磁共振研究所以及哥本哈根大学医院) Hawkes Institute, University College London(霍克斯研究所和伦敦大学学院) Computer Science and AI Laboratory, Massachusetts Institute of Technology(麻省理工学院计算机科学与人工智能实验室)

AI总结 本文提出了一种可扩展的框架,通过回归有符号距离图,在神经影像中实现3D分割的高分辨率上采样,提升了模型的泛化能力和可扩展性。

Comments 13 pages, 4 figures

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2511.17481 2025-11-24 cs.CV

Counterfactual World Models via Digital Twin-conditioned Video Diffusion

通过数字孪生条件的视频扩散实现反事实世界模型

Yiqing Shen, Aiza Maksutova, Chenjia Li, Mathias Unberath

机构 * Johns Hopkins University(约翰霍普金斯大学)

AI总结 CWMDT通过构建数字孪生和应用大语言模型,实现反事实世界模型,提升对视频正向模拟的控制能力。

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2511.16823 2025-11-24 cs.LG cs.AI cs.HC

Monte Carlo Expected Threat (MOCET) Scoring

蒙特卡洛预期威胁(MOCET)评分

Joseph Kim, Saahith Potluri

机构 * Johns Hopkins University School of Medicine(约翰霍普金斯大学医学院)

AI总结 MOCET是一种可解释且双重可扩展的指标,用于量化大语言模型在现实世界中的安全风险。

Comments Accepted to NeurIPS 2025 BioSafe GenAI

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2511.16662 2025-11-21 cs.CV

TriDiff-4D: Fast 4D Generation through Diffusion-based Triplane Re-posing

TriDiff-4D:通过基于扩散的三平面重定位实现快速4D生成

Eddie Pokming Sheung, Qihao Liu, Wufei Ma, Prakhar Kaushik, Jianwen Xie, Alan Yuille

机构 * Johns Hopkins University(约翰霍普金斯大学) Lambda Inc(Lambda公司)

AI总结 TriDiff-4D通过基于扩散的三平面重定位技术,实现高效可控的4D虚拟人物生成,显著提升生成质量和效率。

Comments 8 pages, 10 figures, Under review at a conference

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2412.17982 2025-11-21 cs.CV

Unsupervised learning of spatially varying regularization for diffeomorphic image registration

无监督学习空间变化的正则化用于变形图像配准

Junyu Chen, Shuwen Wei, Yihao Liu, Zhangxing Bian, Yufan He, Aaron Carass, Harrison Bai, Yong Du

机构 * Department of Radiology and Radiological Science, Johns Hopkins School of Medicine, MD, USA(放射科与放射科学系,约翰霍普金斯医学院,马里兰州,美国) Image Analysis and Communications Laboratory, Department of Electrical and Computer Engineering, Johns Hopkins University, MD, USA(图像分析与通信实验室,电气与计算机工程系,约翰霍普金斯大学,马里兰州,美国) Department of Electrical and Computer Engineering, Vanderbilt University, TN, USA(电气与计算机工程系,范德比尔特大学,田纳西州,美国) NVIDIA Corporation, Santa Clara, CA, USA(英伟达公司,圣克拉拉,加利福尼亚州,美国)

AI总结 本文提出一种分层概率模型,通过端到端学习空间变化的正则化,提升图像配准性能并增强可解释性。

Comments Accepted to Medical Image Analysis ((c) MedIA). Code available at http://bit.ly/3BrXGxz

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2507.17597 2025-11-20 cs.HC cs.CV

Human-AI Collaboration and Explainability for 2D/3D Registration Quality Assurance

Sue Min Cho, Alexander Do, Russell H. Taylor, Mathias Unberath

机构 * Johns Hopkins University(约翰霍普金斯大学)

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2511.14685 2025-11-19 cs.CL astro-ph.IM

Encoding and Understanding Astrophysical Information in Large Language Model-Generated Summaries

Kiera McCormick, Rafael Martínez-Galarza

机构 * Department of Computer Science(计算机科学系) Johns Hopkins University(约翰霍普金斯大学) AstroAI Center for Astrophysics(天体物理中心)

Comments Accepted to the Machine Learning and the Physical Sciences Workshop at NeurIPS 2025, 11 pages, 4 figures

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2511.14100 2025-11-19 cs.CV

Text-Driven Reasoning Video Editing via Reinforcement Learning on Digital Twin Representations

Yiqing Shen, Chenjia Li, Mathias Unberath

机构 * Department of Computer Science, Johns Hopkins University(计算机科学系,约翰霍普金斯大学)

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2511.12668 2025-11-18 cs.CR cs.AI cs.LG

AI Bill of Materials and Beyond: Systematizing Security Assurance through the AI Risk Scanning (AIRS) Framework

Samuel Nathanson, Alexander Lee, Catherine Chen Kieffer, Jared Junkin, Jessica Ye, Amir Saeed, Melanie Lockhart, Russ Fink, Elisha Peterson, Lanier Watkins

机构 * Johns Hopkins University Applied Physics Laboratory (APL)(约翰霍普金斯大学应用物理实验室)

Comments 13 pages, 4 figures, 6 tables

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2511.12371 2025-11-18 cs.CV

Reasoning Text-to-Video Retrieval via Digital Twin Video Representations and Large Language Models

Yiqing Shen, Chenxiao Fan, Chenjia Li, Mathias Unberath

机构 * Department of Computer Science, Johns Hopkins University(计算机科学系,约翰霍普金斯大学)

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2511.12368 2025-11-18 cs.CV

Fast Reasoning Segmentation for Images and Videos

Yiqing Shen, Mathias Unberath

机构 * Department of Computer Science, Johns Hopkins University(计算机科学系,约翰·霍普金斯大学)

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2511.12365 2025-11-18 cs.CV

Constructing and Interpreting Digital Twin Representations for Visual Reasoning via Reinforcement Learning

Yiqing Shen, Mathias Unberath

机构 * Department of Computer Science, Johns Hopkins University(计算机科学系,约翰霍普金斯大学)

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2408.01857 2025-11-18 math.NA cs.LG cs.NA math.OC

Using Linearized Optimal Transport to Predict the Evolution of Stochastic Particle Systems

Nicholas Karris, Evangelos A. Nikitopoulos, Ioannis G. Kevrekidis, Seungjoon Lee, Alexander Cloninger

机构 * University of Michigan(密歇根大学) Johns Hopkins University(约翰霍普金斯大学) California State University, Long Beach(长滩加州州立大学)

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2407.12492 2025-11-18 cs.LG cs.AI cs.CV stat.ML

Temporal Test-Time Adaptation with State-Space Models

Mona Schirmer, Dan Zhang, Eric Nalisnick

机构 * UvA-Bosch Delta Lab, University of Amsterdam(阿姆斯特丹大学) Bosch Center for AI(博世人工智能中心) Johns Hopkins University(约翰霍普金斯大学)

Comments Published in Transactions on Machine Learning Research (TMLR)

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2511.11787 2025-11-18 astro-ph.IM cs.CV cs.LG

Towards Mitigating Systematics in Large-Scale Surveys via Few-Shot Optimal Transport-Based Feature Alignment

Sultan Hassan, Sambatra Andrianomena, Benjamin D. Wandelt

机构 * Space Telescope Science Institute(太空望远镜科学研究所) South African Radio Astronomy Observatory(南非射电天文台) University of the Western Cape(南非西部大学) Johns Hopkins University(约翰霍普金斯大学)

Comments 5 pages, 3 figures, accepted to NeurIPS Workshop on Unifying Representations in Neural Models (UniReps 2025)

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2508.09649 2025-11-18 cs.CV

The Brain Resection Multimodal Image Registration (ReMIND2Reg) 2025 Challenge

Reuben Dorent, Laura Rigolo, Colin P. Galvin, Junyu Chen, Mattias P. Heinrich, Aaron Carass, Olivier Colliot, Demian Wassermann, Alexandra Golby, Tina Kapur, William Wells

机构 * Inria Saclay Île-de-France(法国里昂萨克利研究所) CEA(法国原子能委员会) Université Paris-Saclay(巴黎-萨克利大学) Sorbonne Université(索邦大学) Institut du Cerveau - Paris Brain Institute - ICM(巴黎脑研究所) CNRS(法国国家科学研究中心) Inria(法国国家信息与自动化技术研究所) Inserm(法国国家医学研究院) AP-HP(法国国家医院集团) Hôpital de la Pitié Salpêtrière(皮蒂埃-萨尔普里埃尔医院) Harvard Medical School(哈佛医学院) Brigham and Women's Hospital(布里根医院) Department of Radiology and Radiological Science(放射学与放射科学系) Johns Hopkins Medical School(约翰霍普金斯医学院) Institute of Medical Informatics(医学信息学研究所) University of Lübeck(吕贝克大学) Image Analysis and Communications Laboratory(图像分析与通信实验室) Department of Electrical and Computer Engineering(电气与计算机工程系) Johns Hopkins University(约翰霍普金斯大学) CSAIL(媒体实验室)

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2503.02034 2025-11-14 cs.CV cs.AI

Abn-BLIP: Abnormality-aligned Bootstrapping Language-Image Pre-training for Pulmonary Embolism Diagnosis and Report Generation from CTPA

Zhusi Zhong, Yuli Wang, Lulu Bi, Zhuoqi Ma, Sun Ho Ahn, Christopher J. Mullin, Colin F. Greineder, Michael K. Atalay, Scott Collins, Grayson L. Baird, Cheng Ting Lin, Webster Stayman, Todd M. Kolb, Ihab Kamel, Harrison X. Bai, Zhicheng Jiao

机构 * Department of Diagnostic Imaging, Brown University Health(布朗大学健康中心诊断影像科) Warren Alpert Medical School of Brown University(布朗大学沃伦·阿尔珀特医学院) Department of Biomedical Engineering, Johns Hopkins University School of Medicine(约翰霍普金斯大学医学院生物医学工程系) Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine(约翰霍普金斯大学医学院放射科) Johns Hopkins University Division of Pulmonary and Critical Care Medicine(约翰霍普金斯大学肺科与重症医学科) Department of Radiology, University of Colorado School of Medicine(科罗拉多大学医学院放射科)

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2511.09475 2025-11-13 cs.LG

Enhancing Explainability in Solar Energetic Particle Event Prediction: A Global Feature Mapping Approach

Anli Ji, Pranjal Patil, Chetraj Pandey, Manolis K. Georgoulis, Berkay Aydin

机构 * Dept. of Computer Science, California State University, Fullerton, CA, USA(加州州立大学富尔顿分校计算机科学系) Dept. of Computer Science, Georgia State University, Atlanta, GA, USA(佐治亚州立大学计算机科学系) Dept. of Computer Science, Texas Christian University, Fort Worth, TX, USA(德克萨斯基督教大学计算机科学系) Applied Physics Laboratory, Johns Hopkins University, Laurel, MD, USA(约翰霍普金斯大学应用物理实验室)

Comments 10 pages, 3 Figures. This is a pre-print of an accepted paper at ICDMW: SABID 2025

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2511.07419 2025-11-13 cs.LG

Routing Manifold Alignment Improves Generalization of Mixture-of-Experts LLMs

Zhongyang Li, Ziyue Li, Tianyi Zhou

机构 * Johns Hopkins University(约翰霍普金斯大学) University of Maryland, College Park(马里兰大学学院公园分校)

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2510.23749 2025-11-13 astro-ph.IM cs.LG

Re-envisioning Euclid Galaxy Morphology: Identifying and Interpreting Features with Sparse Autoencoders

John F. Wu, Michael Walmsley

机构 * Space Telescope Science Institute(太空望远镜科学研究所) Johns Hopkins University(约翰霍普金斯大学) University of Toronto(多伦多大学)

Comments Authors contributed equally to this work. Accepted to NeurIPS Machine Learning and the Physical Sciences Workshop. See trained model at https://huggingface.co/mwalmsley/euclid-rr2-mae, HuggingFace demo at https://huggingface.co/spaces/mwalmsley/euclid_masked_autoencoder, and code at https://github.com/jwuphysics/euclid-galaxy-morphology-saes

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2505.04529 2025-11-13 cs.CV

RAFT -- A Domain Adaptation Framework for RGB & LiDAR Semantic Segmentation

Edward Humes, Xiaomin Lin, Boxun Hu, Rithvik Jonna, Tinoosh Mohsenin

机构 * Department of Electrical and Computer Engineering, Johns Hopkins University(约翰霍普金斯大学电气与计算机工程系) Department of Electrical Engineering, University of South Florida(佛罗里达州立大学电气工程系)

Comments Submitted to RA-L

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2507.07965 2025-11-13 cs.LG stat.ML

Prospective Learning in Retrospect

Yuxin Bai, Cecelia Shuai, Ashwin De Silva, Siyu Yu, Pratik Chaudhari, Joshua T. Vogelstein

机构 * Johns Hopkins University(约翰霍普金斯大学) University of Pennsylvania(宾夕法尼亚大学)

Comments Accepted to AGI 2025

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2511.08490 2025-11-12 cs.RO

A Supervised Autonomous Resection and Retraction Framework for Transurethral Enucleation of the Prostatic Median Lobe

Mariana Smith, Tanner Watts, Susheela Sharma Stern, Brendan Burkhart, Hao Li, Alejandro O. Chara, Nithesh Kumar, James Ferguson, Ayberk Acar, Jesse F. d'Almeida, Lauren Branscombe, Lauren Shepard, Ahmed Ghazi, Ipek Oguz, Jie Ying Wu, Robert J. Webster, Axel Krieger, Alan Kuntz

机构 * Laboratory for Computational Sensing and Robotics, Johns Hopkins University(计算感知与机器人实验室,约翰霍普金斯大学) Department of Mechanical Engineering, Vanderbilt University(机械工程系,范德比尔特大学) Department of Computer Science, Vanderbilt University(计算机科学系,范德比尔特大学) Department of General Surgery, Vanderbilt University Medical Center(外科学系,范德比尔特大学医学中心) Virtuoso Surgical(Virtuoso手术公司) Department of Urology, Johns Hopkins University James Buchanan Brady Urological Institute(泌尿外科系,约翰霍普金斯大学詹姆斯·布坎南·布里克泌尿外科研究所)

Comments Submitted to International Symposium on Medial Robotics (ISMR) 2026. 7 pages, 8 figures

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2511.08438 2025-11-12 astro-ph.CO astro-ph.IM cs.LG

Galactification: painting galaxies onto dark matter only simulations using a transformer-based model

Shivam Pandey, Christopher C. Lovell, Chirag Modi, Benjamin D. Wandelt

机构 * Department of Physics and Astronomy, Johns Hopkins University(约翰霍普金斯大学物理与天文学系) Kavli Institute for Cosmology, University of Cambridge(剑桥大学卡弗利宇宙研究所) Center for Cosmology and Particle Physics, New York University(纽约大学宇宙与粒子物理中心)

Comments 8 pages, 4 figures. , accepted at Machine Learning and the Physical Sciences Workshop at NeurIPS 2025

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