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3 papers in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

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The hidden advantage of mask resampling: a theory of masked autoencoders
Oct 1, 2026Jorge Medina Moreira, Lorenzo Bardone, Lenka Zdeborová3D Masked Autoencoders Autoencoder Architectures
Statistical Physics of Computation Laboratory, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
Triangular Resampling for Long-Horizon Motion Generation
Sep 28, 2026Kunhang Li, Yiyi Cai, Xiangyue Zhang +5Denoising Trajectory Diffusion Models
The University of Tokyo · Alaya Lab · Japan Advanced Institute of Science and Technology
When Fusion Fails: Corruption-Aware Rebalanced Fusion for Multi-Modal Medical Image Segmentation
Sep 9, 2026Yuchen Pei, Xiaoyu Hu, Yixiong Zou +5Semi-Supervised Medical Image Segmentation Multimodal Fusion
Central China Normal University Wuhan, China · Huazhong University of Science and Technology Wuhan, China · Guangzhou University of Chinese Medicine Guangzhou, China +2
Does Fault Localization Beat a Fresh Attempt? A Placebo-Controlled Study of Test-Guided Code Repair
Sep 1, 2026Anik JhaRepair Fault Diagnosis
Independent Researcher
LLMODE: Aligning ODEs with LLMs via Gated Token Injection for Irregular Spatio-Temporal Forecasting
Aug 30, 2026Di Zhang, Jingyang Zhang, Ziqian Wang +4Spatio-Temporal Forecasting Latent Trajectories
Beihang University Beijing, China
Refining Over Resampling: Test-Time Self-Correction for LLM Reasoning
Aug 6, 2026Ahsan Bilal, Muhammad Ahmed Mohsin, Muhammad Umer +4LLM Reasoning Strategies Test Time
University of Oklahoma · Stanford University · Universitat Pompeu Fabra +1
Try Again, Don't Look Back: Blind Resampling Outperforms Self-Repair in Small Code Models
Jul 28, 2026Yuvraj VermaRetrying Self-Repair
Independent Researcher, India.
The Dimension of Nonterminating Resampling Computations
Jul 20, 2026Yunbei XuTractability Random
National University of Singapore
Where Does the Noise Come From? A Variance-Components Decomposition of Non-Determinism in LLM Brand Answers
Jul 14, 2026Dmitrij ŻatuchinLarge Language Model Reliability Brand-As-Memory
Department of Information Technologies, Estonian Entrepreneurship University of Applied Sciences (EUAS), Tallinn, Estonia. · Rankfor.AI, Wroclaw, Poland; Tallinn, Estonia.
Resample or Reroute? Recoverable Stopping Debt Without Identified Action Selection
Jul 9, 2026Teng-Ruei ChenLarge Language Model Routing Token Budget Allocation
Institute of Bioinformatics and Systems Biology, National Yang Ming Chiao Tung University, Hsinchu, Taiwan · Krixvon, Taipei, Taiwan
Towards Accurate and Fast Clinical Body Composition: A Resource-Efficient Hierarchical Segmentation Framework for Multi-Source CT
Jul 8, 2026Xiaodi Shen, Qingzhu Zheng, Yaoyang Qiu +12Multi Organ Computed Tomography Segmentation Cone-Beam Computed Tomography
Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou 510080, China · Research & Development Center, Canon Medical Systems (China) Co. Ltd. Beijing 100015, China
tsbootstrap: Distribution-Free Uncertainty Quantification and Conformal Prediction for Time Series
Jul 7, 2026Sankalp GildaModel-Based Bootstrap Time Series
DeepThought Solutions
Towards Voxel Spacing Consistency for Medical Image Segmentation
Jun 30, 2026Xin You, Runze Yang, Minghui Zhang +6Voxel Resampling
MS-Resampler: Multi-Scope Visual Resampling for Efficient Multimodal LLMs
Jun 30, 2026Zhongyang Li, Yaqian Li, Faming Fang +6Multimodal Large Language Models Recent Vision-Language Models
Li Auto Inc. · East China Normal University.
The Hidden Cost of Resampling: How Imbalance Correction Degrades Probability Calibration in Tree Ensembles
Jun 29, 2026Zewen LiuOversampling Imbalanced Classification
Qilu Institute of Technology · Tai’an, Shandong, China
Rendering Novel Views of MRI Using 3D Gaussian Splatting
Jun 24, 2026Robin Y. Park, Mark C. Eid, Rhydian Windsor +4Magnetic Resonance Imaging Anatomy
Visual Geometry Group, University of Oxford · Oxford Machine Learning in NeuroImaging Lab, University of Oxford
QC-SMOTE: Quality-Controlled SMOTE for Imbalanced Classification
Jun 23, 2026Parth Upman, Shreyank N GowdaOversampling Imbalanced Classification
School of Computer Science, University of Nottingham, Jubilee Campus, Wollaton Road, Nottingham, NG8 1BB, United Kingdom
Provenance-Grounded Gating and Adaptive Recovery in Synthetic Post-Training Data Curation
Jun 9, 2026Soham Bhattacharjee, Karun Sharma, Vinay Kumar Sankarapu +1Post-Training Data-Curation
Lexsi Labs
G2G: Exploiting Intra-Group Geometry for Inter-Group Pose Estimation
Jun 6, 2026Yufei Wei, Shuhao Ye, Chenxiao Hu +5Category-Level Object Pose Estimation Visual Inertial Odometry
State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou, China · Zhejiang Humanoid Robot Innovation Center Co., Ltd., Ningbo, China · School of Information Science and Engineering, Hangzhou Normal University, Hangzhou, China
PMC-InterCPT: Rethinking Biomedical Interleaved Data for Multimodal Continued Pretraining
May 31, 2026Guanghao Zhu, Zeyu Liu, Zhitian Hou +9Multimodal Clinical Data Multimodal Pretraining
The Hong Kong Polytechnic University · Sun Yat-sen University · PolyU-Daya Bay Technology and Innovation Research Institute
Cluster Analysis with Resampling for Validation and Exploration (CARVE)
May 29, 2026Kai R. Wycik, Tiffany M. Tang, Tarek M. Zikry +1Clustering Cluster
Department of Statistics, Columbia University, New York, NY, USA · Center for Theoretical Neuroscience, Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA · Department of Applied and Computational Mathematics and Statistics, University of Notre Dame, Notre Dame, IN, USA +2
Few-Shot Resampling for Scalable Statistically-Sound Data Mining
May 29, 2026Leonardo Pellegrina, Fabio VandinData Mining Resampling
Department of Information Engineering, University of Padova Padova, Italy
PARCEL: Pool-Anchored Resampling with Conditioned Elastic Queries for Efficient Vision-Language Understanding
May 28, 2026Selim Kuzucu, Alessio Tonioni, Vasile Lup +3Token Compression Recent Vision-Language Models
Max Planck Institute for Informatics, SIC · Google · Technical University of Munich
Retrying vs Resampling in AI Control
May 25, 2026James Lucassen, Adam KaufmanRetrying Artificial Intelligence Safety
Redwood Research
Variance-Reduced Manifold Sampling via Polynomial-Maximization Density Estimation
May 19, 2026Serhii ZabolotniiDensity Ratio Estimation Monte Carlo
Department of Information, Multimedia Technologies and Design, Cherkasy State Business College, Cherkasy, 18028, Ukraine · State Scientific Research Institute of Armament and Military Equipment Testing and Certification, Cherkasy, Ukraine · Department of Cybernetics and Applied Mathematics, Uzhhorod National University, Uzhhorod, Ukraine
Data Presentation Over Architecture: Resampling Strategies for Credit Risk Prediction with Tabular Foundation Models
May 18, 2026Aditya Tanna, Mitul Solanki, Mohamed Bouadi +3Credit Risk Prediction Tabular Foundation Models
Lexsi Labs
Simple Approximation and Derivative Free Inference-Time Scaling for Diffusion Models via Sequential Monte Carlo on Path Measures
May 18, 2026Chenyang Wang, Weizhong Wang, Yinuo Ren +2Diffusion Models Monte Carlo
School of Mathematical Sciences, Peking University, Beijing, China · School of Mathematical Sciences, Fudan University, Shanghai, China · Institute for Computational & Mathematical Engineering, Stanford University, Stanford, CA, United States +2
Probing into Camera Control of Video Models
May 14, 2026Chen Hou, Christian RupprechtVideo Diffusion Models Camera Control
Visual Geometry Group · Visual Geometry Group University of Oxford
A Resampling-Based Framework for Network Structure Learning in High-Dimensional Data
May 12, 2026Ziwei Huang, Zeyuan Song, Paola Sebastiani +1High-Dimensional Resampling
Department of Physics, Boston University, Boston, MA · Division of Computational Biomedicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA · Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA +4
Learning Discriminators for Resampling in the Ensemble Gaussian Mixture Filter through a Normalizing Flow Approach
May 1, 2026Zain Jabbar, Andrey A. PopovParticle Filters Normalizing Flows
R $^3$ -SQL: Ranking Reward and Resampling for Text-to-SQL
Apr 28, 2026Hojae Han, Yeonseok Jeong, Seung-won Hwang +2Text-To-Sql Sql
ETRI · 2Seoul National University · 3Snowflake AI Research
Dilated CNNs for Periodic Signal Processing: A Low-Complexity Approach
Apr 23, 2026Eli Gildish, Michael Grebshtein, Igor MakienkoGraph Signal Processing Waveforms
RSL Electronics LTD, Migdal Ha'Emek, 23100, Israel
Synthetic Data in Education: Empirical Insights from Traditional Resampling and Deep Generative Models
Apr 22, 2026Tapiwa Amion Chinodakufa, Ashfaq Ali Shafin, Khandaker Mamun AhmedSynthetic Data Distributional Fidelity
The Beacom College of Computer & Cyber Sciences, Dakota State University · Knight Foundation School of Computing & Information Sciences, Florida International University
Model-Agnostic Meta Learning for Class Imbalance Adaptation
Apr 20, 2026Hanshu Rao, Guangzeng Han, Xiaolei HuangImbalanced Classification Class Imbalance
University of Memphis
Interpolating Discrete Diffusion Models with Controllable Resampling
Apr 19, 2026Marcel Kollovieh, Sirine Ayadi, Stephan GünnemannDiffusion Models Resampling
School of Computation, Information and Technology, Technical University of Munich
End-to-End Training for Autoregressive Video Diffusion via Self-Resampling
Dec 17, 2025Yuwei Guo, Ceyuan Yang, Hao He +5Autoregressive Video Diffusion Models Resampling
The Chinese University of Hong Kong, Hong Kong, China · ByteDance Seed, China · ByteDance, China
Track and Caption Any Motion: Open-Vocabulary Spatiotemporal Captioning via Trajectory-Conditioned Generation
Dec 11, 2025Bishoy Galoaa, Sarah OstadabbasVideo Captioning Camera Trajectories
Northeastern University

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The hidden advantage of mask resampling: a theory of masked autoencoders

Jorge Medina Moreira, Lorenzo Bardone, Lenka Zdeborová

Statistical Physics of Computation Laboratory, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland

3D Masked Autoencoders Autoencoder Architectures Resampling Residual Learning Theory Diversity

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Why can masked prediction learn useful representations that unmasked reconstruction misses? We study this question in a high-dimensional model of a masked autoencoder (MAE) trained on data with shared latent structure and heterogeneous noise. We prove that masked linear reconstruction can recover the latent feature at linear sample complexity in regimes where unmasked linear reconstruction, equivalent to PCA, fails. The analysis also quantifies the statistical advantage of mask resampling, an established ingredient of masked pretraining. By introducing a fixed collection of

K

masks per sample, we characterize its effect on feature recovery and downstream performance, identifying regimes where greater mask diversity lowers sample complexity. Guided by this prediction, we find that random cropping and flipping in standard image-training pipelines can obscure the advantage of mask resampling by renewing the prediction task even when the patch mask is fixed. Removing these transformations reveals a downstream advantage for dynamic over static masking in CNN autoencoders and vision transformers. A complementary BERT pilot finds benefits from greater mask diversity on downstream language tasks. Our results separate the benefit of the masked prediction objective from that of mask diversity, and show how a tractable theory can guide experiments that uncover advantages hidden by standard training practices.

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