Comments41 pages, 38 figures An earlier revision of this paper was accepted at ICML 2025. Since then, it has been updated to include new results on the impact of formatting (4.4), new dataset (4.6), training dynamics (4.7) and base models (4.8) Extended version of the paper waspublished in Nature 2026/1
ELECTRA: A Cartesian Network for 3D Charge Density Prediction with Floating Orbitals
ELECTRA:一种用于3D电荷密度预测的笛卡尔网络
Jonas Elsborg, Luca Thiede, Alán Aspuru-Guzik, Tejs Vegge, Arghya Bhowmik
机构
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Technical University of Denmark(丹麦技术大学)
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CAPeX Pioneer Center for Accelerating P2X Materials Discovery(CAPeX先锋中心)
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University of Toronto(多伦多大学)
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Vector Institute for Artificial Intelligence(人工智能矢量研究所)
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Canadian Institute for Advanced Research (CIFAR)(加拿大高级研究 institute)
NLP for Social Good: A Survey and Outlook of Challenges, Opportunities, and Responsible Deployment
为社会公益服务的NLP:挑战、机遇与负责任部署的综述与展望
Antonia Karamolegkou, Angana Borah, Eunjung Cho, Sagnik Ray Choudhury, Martina Galletti, Pranav Gupta, Oana Ignat, Priyanka Kargupta, Neema Kotonya, Hemank Lamba, Sun-Joo Lee, Arushi Mangla, Ishani Mondal, Fatima Zahra Moudakir, Deniz Nazarova, Poli Nemkova, Dina Pisarevskaya, Naquee Rizwan, Nazanin Sabri, Keenan Samway, Dominik Stammbach, Anna Steinberg, David Tomás, Steven R Wilson, Bowen Yi, Jessica H Zhu, Arkaitz Zubiaga, Anders Søgaard, Alexander Fraser, Zhijing Jin, Rada Mihalcea, Joel R. Tetreault, Daryna Dementieva
机构
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University of Copenhagen(哥本哈根大学)
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University of Michigan-Ann Arbor(密歇根大学安娜堡分校)
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ETH Zurich(苏黎世联邦理工学院)
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University of North Texas(北卡罗来纳州立大学)
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Sony Computer Science Laboratories - Paris(索尼计算机科学实验室-巴黎)
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Santa Clara University(圣克拉拉大学)
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University of Illinois Urbana-Champaign(伊利诺伊大学厄巴纳-香槟分校)
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Dataminr(DataMinr公司)
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United Nations Development Programme (UNDP)(联合国开发计划署)
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University of Maryland, College Park(马里兰大学学院市分校)
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Max Planck Institute for Intelligent Systems, Tübingen(智能系统马克斯·普朗克研究所,图宾根)
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Vector Institute(向量研究所)
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University of Toronto(多伦多大学)
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University of Washington(华盛顿大学)
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Queen Mary University of London(伦敦大学玛丽女王学院)
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IIT Kharagpur(印度理工学院Kharagpur分校)
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University of California San Diego(加州大学圣地亚哥分校)
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Princeton University(普林斯顿大学)
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LMU Munich(慕尼黑大学)
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Munich Center for Machine Learning (MCML)(慕尼黑机器学习中心)
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University of Alicante(阿利坎特大学)
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University of Michigan-Flint(密歇根大学弗林特分校)
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University of Southern California(南加州大学)
;
Technical University of Munich(慕尼黑技术大学)
机构
*
University of Alberta(阿尔伯塔大学)
;
University of Toronto(多伦多大学)
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Zhejiang University(浙江大学)
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School of Computer Science McGill University(麦吉尔大学计算机学院)
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Alibaba Group (Ant Group)(阿里巴巴集团(蚂蚁集团))
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Chinese Academy of Sciences(中国科学院)
Another look at statistical inference with machine learning-imputed data
对利用机器学习插补数据的统计推断的再审视
Jessica Gronsbell, Jianhui Gao, Zachary R. McCaw, Yaqi Shi, David Cheng
机构
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Department of Statistical Sciences, University of Toronto(统计科学系,多伦多大学)
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Department of Biostatistics, UNC Chapel Hill(生物统计学系,北卡罗来纳大学教堂山分校)
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Biostatistics Center, Massachusetts General Hospital(麻省总医院生物统计中心)
MATTERIX: toward a digital twin for robotics-assisted chemistry laboratory automation
MATTERIX:迈向机器人辅助化学实验室自动化数字孪生
Kourosh Darvish, Arjun Sohal, Abhijoy Mandal, Hatem Fakhruldeen, Nikola Radulov, Zhengxue Zhou, Satheeshkumar Veeramani, Joshua Choi, Sijie Han, Brayden Zhang, Jeeyeoun Chae, Alex Wright, Yijie Wang, Hossein Darvish, Yuchi Zhao, Gary Tom, Han Hao, Miroslav Bogdanovic, Gabriella Pizzuto, Andrew I. Cooper, Alán Aspuru-Guzik, Florian Shkurti, Animesh Garg
机构
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University of Toronto(多伦多大学)
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Acceleration Consortium(加速联盟)
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Vector Institute(向量研究所)
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University of Liverpool(利物浦大学)
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University of Salento(萨勒诺大学)
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NVIDIA Canadian Institute for Advanced Research(NVIDIA加拿大高级研究机构)
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Georgia Institute of Technology(佐治亚理工学院)
CommentsDarvish, K., Sohal, A., Mandal, A. et al. MATTERIX: toward a digital twin for robotics-assisted chemistry laboratory automation. Nat Comput Sci (2025)
TreeWriter: AI-Assisted Hierarchical Planning and Writing for Long-Form Documents
TreeWriter: 人工智能辅助的长篇文档分层规划与写作
Zijian Zhang, Fangshi Du, Xingjian Liu, Pan Chen, Oliver Huang, Runlong Ye, Michael Liut, Alán Aspuru-Guzik
机构
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Department of Computer Science, University of Toronto, Sandford Fleming Building, 10 King’s College Road, ON M5S 3G4, Toronto, Canada
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Vector Institute for Artificial Intelligence, 661 University Ave. Suite 710, ON M5G 1M1, Toronto, Canada
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Department of Chemistry, University of Toronto, Lash Miller Chemical Laboratories, 80 St. George Street, ON M5S 3H6, Toronto, Canada
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Department of Mathematical
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Computational Sciences, University of Toronto Mississauga, 3359 Mississauga Road, Deerfield Hall, ON L5L 1C6, Mississauga, Canada
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Department of Materials Science \& Engineering, University of Toronto, 184 College St., M5S 3E4, Toronto, Canada
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Department of Chemical Engineering \& Applied Chemistry, University of Toronto, 200 College St. ON M5S 3E5, Toronto, Canada
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Acceleration Consortium, 700 University Ave., M7A 2S4, Toronto, Canada
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Canadian Institute for Advanced Research (CIFAR), 661 University Ave., M5G 1M1, Toronto, Canada
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NVIDIA, 431 King St W \#6th, M5V 1K4, Toronto, Canada
Press Start to Charge: Videogaming the Online Centralized Charging Scheduling Problem
按下开始按钮充电:将在线集中充电调度问题游戏化
Alireza Ghahtarani, Martin Cousineau, Amir-massoud Farahmand, Jorge E. Mendoza
机构
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Department of Logistics and Operations Management, HEC Montréal(物流与运营管理系,蒙特利尔HEC商学院)
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Department of Computer Science, University of Toronto(计算机科学系,多伦多大学)
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Department of Computer Engineering and Software Engineering, Polytechnique Montréal(计算机工程与软件工程系,蒙特利尔Polytechnique大学)
Normalized Conditional Mutual Information Surrogate Loss for Deep Neural Classifiers
归一化条件互信息替代损失用于深度神经分类器
Linfeng Ye, Zhixiang Chi, Konstantinos N. Plataniotis, En-hui Yang
机构
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Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Canada(滑铁卢大学电气与计算机工程系)
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The Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, Toronto, Canada(多伦多大学Edward S. Rogers Sr.电气与计算机工程系)
Uncertainty Quantification From Scaling Laws in Deep Neural Networks
深度神经网络中从缩放定律量化不确定性
Ibrahim Elsharkawy, Yonatan Kahn, Benjamin Hooberman
机构
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Department of Physics, University of Illinois Urbana-Champaign, Urbana, IL, USA(伊利诺伊大学厄巴纳-香槟分校物理系)
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Department of Physics, University of Toronto, Toronto, ON, Canada(多伦多大学物理系)
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Vector Institute, Toronto, ON, Canada(向量研究所)
Cell Behavior Video Classification Challenge, a benchmark for computer vision methods in time-lapse microscopy
细胞行为视频分类挑战,一种用于时间延拓显微镜中计算机视觉方法的基准测试
Raffaella Fiamma Cabini, Deborah Barkauskas, Guangyu Chen, Zhi-Qi Cheng, David E Cicchetti, Judith Drazba, Rodrigo Fernandez-Gonzalez, Raymond Hawkins, Yujia Hu, Jyoti Kini, Charles LeWarne, Xufeng Lin, Sai Preethi Nakkina, John W Peterson, Koert Schreurs, Ayushi Singh, Kumaran Bala Kandan Viswanathan, Inge MN Wortel, Sanjian Zhang, Rolf Krause, Santiago Fernandez Gonzalez, Diego Ulisse Pizzagalli
机构
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Euler Institute, Faculty of Informatics, Università della Svizzera italiana(欧拉研究所,信息学院,瑞士大学)
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International Center for Advanced Computing in Medicine (ICAM), University of Pavia(国际医学先进计算中心(ICAM),帕维亚大学)
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Imaging Platform, ACRF INCITe Centre, Garvan Institute of Medical Research(成像平台,ACRF INCITe中心,嘉文医学研究所)
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Tacoma School of Engineering & Technology, University of Washington(塔科马工程与技术学院,华盛顿大学)
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Data Science, Institute for Computing and Information Sciences, Radboud University(数据科学,计算与信息科学研究所,拉德堡德大学)
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Imaging Core, Lerner Research Institute, Cleveland Clinic(成像核心,勒纳研究研究所,克利夫兰诊所)
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Institute of Biomedical Engineering, University of Toronto(生物医学工程研究所,多伦多大学)
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Center for Research in Computer Vision, University of Central Florida(计算机视觉研究中心,佛罗里达大学)
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Computational Biology Group, Data Science Platform, Garvan Institute of Medical Research(计算生物学小组,数据科学平台,嘉文医学研究所)
From Prompt to Protocol: Fast Charging Batteries with Large Language Models
从提示到协议:利用大语言模型实现快速充电电池
Ge Lei, Ferran Brosa Planella, Sterling G. Baird, Samuel J. Cooper
机构
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Dyson School of Design Engineering, Imperial College London(帝国理工学院伦敦设计工程学院)
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University of Warwick(沃里克大学)
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Acceleration Consortium, University of Toronto(多伦多大学加速联盟)
From Performance to Practice: Knowledge-Distilled Segmentator for On-Premises Clinical Workflows
从性能到实践:面向本地临床工作流的知识蒸馏分割器
Qizhen Lan, Aaron Choi, Jun Ma, Bo Wang, Zhaogming Zhao, Xiaoqian Jiang, Yu-Chun Hsu
机构
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D. Bradley McWilliams School of Biomedical Informatics(D. Bradley McWilliams 生物医学信息学学院)
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The University of Texas Health Science Center at Houston(德克萨斯大学健康科学中心休斯顿分校)
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M31 AI
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University Health Network(大学健康网络)
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University of Toronto(多伦多大学)
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Vector Institute(向量研究所)
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Center for Precision Health(精准健康中心)
Sliced-Wasserstein Distribution Alignment Loss Improves the Ultra-Low-Bit Quantization of Large Language Models
切片瓦瑟斯坦分布对齐损失提高了大语言模型的超低比特量化
Deyu Cao, Yixin Yin, Samin Aref
机构
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Department of Information and Communication Engineering, The University of Tokyo(信息与通信工程系,东京大学)
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Department of Computer Science, University of Toronto(计算机科学系,多伦多大学)
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Department of Mechanical and Industrial Engineering, University of Toronto(机械与工业工程系,多伦多大学)
AI总结
切片瓦瑟斯坦分布对齐损失通过提升超低比特量化性能,有效恢复模型准确性。
CommentsPost-peer-review accepted manuscript, 17 pages including the supplementary information