Self-Supervised Learning

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Period ending 2026-09-07

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A weekly snapshot of new work published in Self-Supervised Learning.

237 papers

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Which Pretext Task Transfers? Self-Supervised Pretraining Objectives for Lung Ultrasound
Sep 15, 2026Moein Heidari, Junbo Rao, Jai Choraria +3Ultrasound Self-Supervised Learning
MAST: Label-Efficient, Robust, and Generalizable Sound Detection for Biodiversity Monitoring via Masked Audio Pretraining and Self-Training
Sep 14, 2026Tianyi Xu, Daniel Pimentel-Alarcón, Zuzana Buřivalová +1Acoustic Sensing Self-Supervised Learning
Does Attention-Guided Masking Really Help Object Discovery in Object-Centric Learning?
Sep 14, 2026Youliang Tao, Yanhua Han, Bin Zhao +3Attention-Guided Transunet Self-Supervised Learning
Self-supervised Pre-training Helps Retinal Disease Progression Modelling Most When Data Is Scarce
Sep 14, 2026Ifeoma Veronica Nwabufo, Julius Gervelmeyer, Sarah Müller +1Self-Supervised Learning Retinal Imaging
Is Semantics Enough for Speech Mean Opinion Score Prediction?
Sep 3, 2026Tianyu Lan, Yufei Shi, Yang Ai +3Speaker Identity Neural Audio Codecs
Pix2Rep-v2: Data-Efficient Representation Learning for Dense Medical Imaging Applications
Sep 1, 2026S. Sifaoui, E. Angelini, S. Toupin +2Dense Prediction Medical Imaging
Physics-Driven Independent Pair Generation for Iterative Self-Supervised Low-Dose CT Denoising
Sep 1, 2026Xianlei Han, Shaoyu Wang, Jiancheng Fang +2Positron Emission Tomography Computed Tomography
Three Steps at a Time: Learning Representations from Action Sequences in Contrastive RL
Aug 31, 2026Michal Korniak, Kamil Dybek, Benjamin Eysenbach +2Action Chunks Representation Learning
Self-Supervised Pretext Tasks for Infant Cry Analysis: A Controlled Comparison and a Cautionary Result on Donateacry
Aug 31, 2026Luigi SimeoneAudio Classification Self-Supervised Speech Models
Scalable Self-Supervised Learning for Multiphase AC-OPF in Distribution Systems with Topology Reconfiguration
Aug 25, 2026Hoang T. Nguyen, Shaohui Liu, Reetam Sen Biswas +4Ac Optimal Power Flow Reconfigurable
A Controlled Study of Self-Supervised Image and Video Pretraining under Limited Resources
Aug 13, 2026Brunó B. Englert, Gijs DubbelmanSelf-Supervised Learning Vision Foundation Models
Fourier Self-Supervision for Fine-Grained Generalized Category Discovery
Aug 9, 2026Sarah Rastegar, Mina Ghadimi Atigh, Pascal Mettes +2Generalized Category Discovery Fine-Grained Perception
Three Necessary Principles for Self-Supervised Visual Representation Learning
Aug 8, 2026Nikos Giakoumoglou, Paschalis Giakoumoglou, Tania StathakiSelf-Supervised Representations Self-Supervised Learning
Vernata: Self-Supervised Learning of LiDAR Point Representations
Aug 7, 2026Oliver Lemke, Alexander Liniger, Abel Gawel +1Light Detection And Ranging Point Clouds Light Detection And Ranging
Is Self-Pretraining really useful to improve diagnosis in medical Time Series?
Aug 6, 2026Omar Coser, Antonio Orvieto, Paolo Soda +1Time-Series Classification Time Series
Spectral Aliasing Pretext: A novel task for Self-Supervised fault diagnosis in rotating machinery
Aug 6, 2026Victor Gialis, Maxime Metz, David Esteve +1Fault Diagnosis Self-Supervised Learning
Lesion Detection in CT with Frozen Self-Distilled Features: SALT, a Spatially Adaptive Label-Guided Temperature
Aug 5, 2026Mahmut S. Gokmen, Evan W. Damron, Mitchell A. Klusty +3Lesion Self-Supervised Learning
NodeJEPA: Structure-Conditioned Latent Prediction for Node-Level Graph Self-Supervised Learning
Aug 5, 2026Tinghe Zhang, Jian Xu, Jiaheng Chen +3Joint-Embedding Predictive Architectures Graph Learning
Attention-Only White-Box Transformer via LeJEPA-Based Self-Supervised Pretraining
Aug 4, 2026Yang Bai, Linyuan Wang, Haoyang Jiang +3Self-Supervised Learning Model Pretraining
ED-DiT: Physics-Guided Diffusion Pretraining for Transferable Molecular Representations from Electron Density
Aug 4, 2026Liang Shuang, Haocheng Wang, Jiayi Song +2Density Functional Theory Model Pretraining
Scaling an Autoregressive Transformer for Single-Cell Generation
Aug 3, 2026Aleksandr Sharipov, Yusif Mukhtarov, Igor MolybogAutoregressive Transformers Single-Cell Rna
Self-Supervised Representations for Binary Program Clustering: From Empirical Study to Retrieval-Augmented Learning
Aug 3, 2026Martin Mocko, Daniela ChudáMalware Classification Clustering
Multi-Backbone Self-Supervised Ensembles for Audio Deepfake Detection and a Cross-Track Analysis of Generation-Detection Asymmetry
Aug 3, 2026Seunghyun Kim, Junghyun Kim, Jiyoung WooAudio Deepfake Detection Unsupervised Detectors
Asleep at the Wheel: JEPA's Limitations in Evaluating Novel Driving Data
Aug 2, 2026Advait Pavuluri, Shamik Karkhanis, Uzma MushtaqueNaturalistic Driving Data Self-Supervised Learning
Self Supervised Learning from Automatically Generated Demonstrations for Visual Robotic Manipulation
Aug 1, 2026Andres Rivas, Anselmo R. Cukla, Rodrigo S. Guerra +2Robotic Manipulation Self-Supervised Learning
REIMU: Efficient Heterogeneous Hierarchical Reasoning for SSL-Based Speech Deepfake Detection
Aug 1, 2026Kwok-Ho Ng, Tingting Song, Bingwen Feng +1Audio Deepfake Detection Self-Supervised Speech Models
HP-JEPA: Hierarchical Partitioning for Multi-Resolution Graph Joint-Embedding Predictive Learning
Aug 1, 2026Ruichen Xu, Jingxiang Qu, Wenhan Gao +5Graph Learning Video Joint Embedding Predictive Architecture
Neural Operator Learning for Collision-Aware Trajectory Planning of Spacecraft Swarms
Jul 31, 2026Sidhdharth D. Sikka, Suyi Gao, Zehui Lu +2Unmanned Aerial Vehicle Swarms Spacecraft
Bootstrapping Self-Supervised Learning of Binary Classification Using Error Bounds: A Case Study on a Robotic Insertion Task
Jul 31, 2026Zebin Duan, Norbert Krüger, Juan Heredia +2Confidence Intervals Self-Supervised Learning
Domain-Division based Progressive Learning for Source-Free Domain Adaptation
Jul 31, 2026Pan Liu, Jing Li, Meng Zhao +3Unsupervised Domain Adaptation Domain Adaptation
Physics-Aligned Self-Supervised Learning for Scientific Imaging
Jul 30, 2026Bashir Kazimi, Stefan SandfeldData Augmentation Self-Supervised Learning
Large scale cross-regional remote sensing flood monitoring framework for operative mapping and impact analysis
Jul 30, 2026Ilya Novikov, Svetlana Illarionova, Ruslan Dzharkinov +6Flood Mapping Flood Detection
Dissecting Sensitivity to Training Language in Self-Supervised Speech Learning Using Neural Audio Codec Tokens
Jul 28, 2026Daigo Takizawa, Tomohiko Nakamura, Samuele Cornell +3Self-Supervised Speech Models Neural Audio Codecs
Mind the Microphone Gap: Benchmarking Array Upsampling Strategies for Latent Acoustic Mapping
Jul 27, 2026Philipp Schmidt, Huw Cheston, Juan Azcarreta +3Acoustic Representation Upsampling
LoTA-N2N: Local Trace Adaptation for Zero-Shot Self-Supervised Image Denoising
Jul 27, 2026Jintong Hu, Bin Xia, Junlin Liu +2Denoising Diffusion Probabilistic Model Self-Supervised Learning
A Scale-adaptive Vision Model Links C. elegans Neuronal Morphology to Behavior for Neurotoxicity Assessment
Jul 25, 2026Haochao Ying, Shenchong Lv, Yutao Sun +8Neuroimaging Models Toxicity
IQ-JEPA: A Joint-Embedding Predictive Architecture with a Hermitian Vision Transformer for Sound Speed and Attenuation Estimation from Ultrasound IQ Data
Jul 24, 2026Masashi Sode, Gianmarco PintonUltrasound Self-Supervised Learning
Unbiased Open World Regularization for Fair Self-Supervised Learning
Jul 24, 2026L{é}o Nicollier, Marc Pic, Pablo Mus{é} +2Self-Supervised Learning Regularization Methods
Self-Supervised Learning of Structured Dynamics from Videos
Jul 23, 2026Lukas Knobel, Andrew Zisserman, Yuki M. AsanoVideo Representation Self-Supervised Learning
MSBraM: A Multi-scale Self-supervised Brain Foundation Model for Hierarchical EEG Dynamics Learning
Jul 23, 2026Tao Zhou, Jing Han, Lingyu Shu +1Electroencephalography Foundation Models Electroencephalogram
Masked Topology Modeling for Self-Supervised Learning on Parametric CAD
Jul 22, 2026Heinrich Jiang, Jennifer JangComputer-Aided Design Topological Learning
Self-supervision drives representational convergence in medical foundation models more than clinical supervision
Jul 22, 2026Soroosh Tayebi Arasteh, Sebastian Ziegelmayer, Mahshad Lotfinia +4Medical Imaging Self-Supervised Learning
DINS-IO: Learned Inertial Odometry via Differentiable INS Consistency
Jul 22, 2026Hao Qiao, Yan Wang, Jian Kuang +1Inertial Odometry Inertial Measurement Units
Sentence Splitter: Uncovering Latent Factual Structure for Self-Supervised Learning
Jul 22, 2026Ahmad Pouramini, Mahsa AfsharizadehNatural Language Processing Knowledge Graph Completion
Physical Self-Supervised Learning: IMU Sensing without Manual Labels
Jul 20, 2026Yuyang Leng, Renyuan Liu, Shaohan Hu +4Self-Supervised Learning Inertial Measurement Units
BrainNext: A General-Purpose Self-Supervised Foundation Model for Brain MRI Analysis
Jul 20, 2026Moona Mazher, Abdul Qayyum, Steven A. Niederer +1Neuroimaging Models Self-Supervised Learning
A Framework for Early Sepsis Prediction via Self-Supervised (JEPA) and Federated Representation Learning
Jul 18, 2026Umair bin Mansoor, Munaf Rashid, Roomi NaqviSepsis Biomarker
Multimodality as Supervision: Self-Supervised Specialization to the Test Environment via Multimodality
Jul 16, 2026Kunal Pratap Singh, Ali Garjani, Rishubh Singh +6Self-Supervised Learning Developmental Trajectories
Leveraging unlabelled data for generalizable neural population decoding
Jul 15, 2026Ximeng Mao, Nanda H. Krishna, Avery Hee-Woon Ryoo +2Neural Recordings Self-Supervised Learning
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training?
Jul 14, 2026Nusrat Munia, Tyler Ward, Nishat Nayla +2Self-Supervised Learning Self-Supervised Representations
Self-supervised training for high-resolution close-range multispectral remote sensing imagery
Jul 13, 2026Leon-Friedrich Thomas, Mikael Änäkkälä, Antti LajunenSwin Remote Sensing
Contrastive Joint-Embedding Prediction for Representation Learning in Structural MRI
Jul 12, 2026Fabian Mager, Lars Kai HansenMagnetic Resonance Imaging Video Joint Embedding Predictive Architecture
Self-supervised Automatic Matting
Jul 11, 2026Xiaonan Hu, Zhiyuan Lu, Jingdong Zhao +1Self-Supervised Learning Image Enhancement
MeloBottleneck: Self-Supervised Melody Skeleton Extraction with a Latent Subsequence Bottleneck
Jul 11, 2026Fan Bu, Rongfeng Li, Linfeng FanSkeletonization Self-Supervised Learning
Tracking Intermittent Particles with Self-Learned Visual Features
Jul 10, 2026Raphael Reme, Victor Piriou, Alison Hanson +5Multi-Object Tracking Microscopy
Lifelong Representations: A Survey on Continual Self-Supervised Learning for Vision Models
Jul 8, 2026Sergi Masip, Alicja Dobrzeniecka, Jonathan Swinnen +4Efficient Continual Learning Self-Supervised Learning
`Attention-Guided Cross-Temporal Clustering for Self-Supervised Video Object Segmentation
Jul 8, 2026Waqas Arshid, Mohammad Awrangjeb, Alan Wee-Chung Liew +1Video Object Segmentation Self-Supervised Learning
Self-Supervised Pretraining Improves Cross-Site and Cross-Scale Robustness of Point Cloud Leaf-Wood Segmentation
Jul 8, 2026Heeju Mun, Tackang Yang, Yunsoo Nam +1Point Clouds Random Forest
InsideSSL: Understanding Self-Supervised Speech Representations using a Model-Centric Perspective
Jul 7, 2026Samir Sadok, Xavier Alameda-PinedaSelf-Supervised Speech Models Wav2Vec
Scalable Perturbation Learning for Online Self-Supervised Echo State Networks
Jul 7, 2026Taiki Yamada, Kantaro FujiwaraSelf-Supervised Learning Reservoir

Sep 15, 2026 · cs.CVJ/K move · Enter open · S save

Which Pretext Task Transfers? Self-Supervised Pretraining Objectives for Lung Ultrasound

Moein Heidari, Junbo Rao, Jai Choraria, Wenjin Chen+2

Self-supervised learning (SSL) can reduce the need for labelled medical images, but the choice of pretext objective remains unclear for lung ultrasound (LUS). Contrastive learning, masked reconstruction, and joint-embedding predictive architectures (JEPA) differ in the space in which their targets are defined, yet existing ultrasound studies compare them under different corpora, backbones, and evaluation protocols. We compare these three objective families using the same encoder backbone, pretraining corpus, optimisation schedule, and frozen-evaluation protocol. Encoders are pretrained on COVID-BLUeS LUS videos and evaluated with linear,

k

NN, and attentive probes at 5%, 10%, 50%, and 100% label budgets. Evaluation is performed on POCUS using patient-level five-fold cross-validation and on the independently acquired Mendeley-Uganda dataset, which is excluded from both pretraining and probe fitting. At the full label budget under linear probing, VideoMAE and V-JEPA achieve

66.5 \pm 13.1

and

65.4 \pm 11.7

balanced accuracy on POCUS, while MoCo achieves

42.1 \pm 1.2

. On Mendeley-Uganda, the ranking reverses: MoCo performs best at

62.7 \pm 1.0

, followed by VideoMAE at

53.8 \pm 2.8

, while V-JEPA falls near chance at

35.1 \pm 4.9

. These results show that POCUS probe accuracy alone does not identify the objective that transfers best across datasets. We also outline planned representation-level analyses to examine this reversal. Code is publicly available at https://github.com/moeinheidari7829/LUSVideoSSL.

Ultrasound Self-Supervised Learning Medical Vision-Language Models

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