Wireless Foundation Models

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Period ending 2026-09-21

8 new papers

A weekly snapshot of new work published in Wireless Foundation Models.

Period ending 2026-09-14

8 new papers

A weekly snapshot of new work published in Wireless Foundation Models.

Period ending 2026-09-07

12 new papers

A weekly snapshot of new work published in Wireless Foundation Models.

309 papers

Latest in Wireless Foundation Models

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InfoAtlas: A Foundation Model for Zero-Shot Statistical Dependence Estimate
May 29, 2026Zhengyang Hu, Yanzhi Chen, Hanxiang Ren +5Mutual Information Temporal Dependence
GraphARC: A Comprehensive Benchmark for Graph-Based Abstract Reasoning
May 29, 2026Saku Peltonen, August Bøgh Rønberg, Andreas Plesner +1Graph Representations Heterogeneous Graph Transformers
AMix-2: Establishing Protein as a Native Modality in Large Language Models
May 29, 2026Keyue Qiu, Yixin Wu, Lihao Wang +19Protein Design Protein Data Bank
GlucoFM: A Dual-Stream Foundation Model for Continuous Glucose Monitoring
May 29, 2026Zechen Li, Keerthana Natarajan, Weizhi Zhang +11Continuous Glucose Monitoring Hypoglycemia Classification
Learning to Extrapolate to New Tasks: A Relational Approach to Task Extrapolation
May 28, 2026Adam Ousherovitch, Yixin WangExtrapolation Wireless Foundation Models
SLAD : Shared LoRA Adapters for Task Specific Distillation
May 28, 2026Reda Bensaid, Yassir Bendou, Vincent Gripon +1Low-Rank Adaptation Adapters Low-Rank Adaptation
The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer
May 28, 2026Tianhua ChenGenerative Models Generative Artificial Intelligence
SpikeWFM: Spiking-Aided Wireless Foundation Model for Robust Channel Prediction
May 28, 2026Liwen Jing, Yisha Lu, Tingting Yang +5Spiking Neural Networks Wireless Foundation Models
LoopFM: Learning frOm HistOrical RePresentations of Foundation Model for Recommendation
May 28, 2026Shali Jiang, Hua Zheng, Boyang Liu +40Knowledge Distillation Wireless Foundation Models
OmniVerifier-M1: Multimodal Meta-Verifier with Explicit Structured Recalibration
May 27, 2026Xinchen Zhang, Bowei Liu, Jiale Liu +7Verification-Triggered Multimodal Multimodal Learning
A Multi-dimensional Framework for Evaluating Generalization in EEG Foundation Models
May 27, 2026Aditya Kommineni, Emily Zhou, Kleanthis Avramidis +2Electroencephalography Foundation Models Wireless Foundation Models
Benchmarking Ultrasound Foundation Models for Fetal Plane Classification
May 27, 2026Leya Barrientos, Yuexi Du, Nicha C. DvornekPrenatal Ultrasound Wireless Foundation Models
SpatialBench: Is Your Spatial Foundation Model an All-Round Player?
May 26, 2026Haosong Peng, Hao Li, Jiaqi Chen +10Geospatial Foundation Models Spatial Representation
Boosting Knowledge Graph Foundation Models via Enhanced Negative Sampling
May 26, 2026Yinan Liu, Wenjin Xu, Zhiyuan Zha +2Knowledge Graph Completion Knowledge Graphs
$R^3$ : 3D Reconstruction via Relative Regression
May 26, 2026Congrong Xu, Huachen Gao, Xingyu Chen +3Feed-Forward 3D Reconstruction 3D Reconstruction
Sparse-LiDAR Prompting of Monocular Geometry Foundations: An Empirical Study Toward Long-Range Driving Depth
May 26, 2026Kai Zheng, Qiang Feng, Xingjian Liu +2Lidar Light Detection And Ranging
Small Models, Strong Priors: Architectural Inductive Bias for Parameter-Efficient Neural PDE Solvers
May 25, 2026Shyam Sankaran, Hanwen Wang, Paris PerdikarisNeural Partial Differential Equation Solvers Neural Architectures
A Clinically Validated Foundation Model for Comprehensive Lung Pathology Interpretation
May 25, 2026Zhengrui Guo, Zhengyu Zhang, Jiabo Ma +23Pathology Foundation Models Non-Small Cell Lung Cancer
DeCoDrift: Stabilizing Decoder Coupling in Closed-Loop Foundation Segmentation
May 25, 2026H. M. Shadman Tabib, Md. Shamsuzzoha Bayzid, M Sohel RahmanLarge Language Model Decoder Attention-Guided Transunet
Discrepancy Minimization Improves Cross-Hospital Robustness in Digital Pathology
May 24, 2026Ben Vardi, Dana Schonberger, Yuval Friedmann +4Pathology Foundation Models Computational Pathology
BandVQ: Band-Wise Vector-Quantized EEG Foundation Model
May 24, 2026Jamiyan Sukhbaatar, Satoshi Imamura, Toshihisa TanakaElectroencephalography Foundation Models Electrocorticography
JT-SAFE-V2: Safety-by-Design Foundation Model with World-Context Data
May 23, 2026Junlan Feng, Fanyu Meng, Chong Long +12Large Language Model Safety Wireless Foundation Models
Assessing the Operational Viability of Foundation Models for Time Series Forecasting
May 23, 2026Kavin Soni, Debanshu Das, Vamshi GuduguntlaTime Series Foundation Models Wireless Foundation Models
Leveraging Foundation Models for Causal Generative Modeling
May 22, 2026Aneesh Komanduri, Xintao WuCausal Foundation Models Causal Reasoning
LWM-CDE: A Representation Space for Wireless Data Reasoning and Transferability
May 22, 2026Sadjad Alikhani, Akshay Malhotra, Shahab Hamidi-Rad +1Transfer Learning Wireless Networks
MARGIN: Runtime Confidence Calibration for Multi-Agent Foundation Model Coordination
May 21, 2026Joss ArmstrongWireless Foundation Models Single-Agent Baselines
CogAdapt: Adapting Clinical ECG Foundation Models for Wearable Cognitive Load Assessment
May 21, 2026Amir Mousavi, Erfan Nourbakhsh, Mohammad Sadegh Sirjani +5Remote Physiological Measurement Cognitive Load
ChronoVAE-HOPE: Beyond Attention -- A Next-Generation VAE Foundation Model for Specialized Time Series Classification
May 21, 2026José Alberto Rodríguez, Luis Balderas, Miguel Lastra +2Time-Series Classification Time Series
The Neglected Baseline in Model Interpretation
May 21, 2026Yongjin Cui, Xiaohui FanInterpretable Models Wireless Foundation Models
Hierarchical Contrastive Learning for Multi-Domain Protein-Ligand Binding
May 19, 2026Shuo Zhang, Rongqi Hong, Huifeng Zhang +1Structure-Based Drug Design Multi-Domain
Synergistic Foundation Models for Semi-Supervised Fetal Cardiac Ultrasound Analysis: SAM-Med2D Boundary Refinement and DINOv3 Semantic Enhancement
May 19, 2026Tonghao Zhuang, Shanglong Hu, Yongsheng Luo +2Whole-Heart Segmentation Prenatal Ultrasound
MSAlign: Aligning Molecule and Mass Spectra Foundation Models for Metabolite Identification
May 19, 2026Paul Krzakala, Gabriel Melo, Camille Lançon +4Tandem Mass Spectra Metabolic
Pocket Foundation Models: Distilling TFMs into CPU-Ready Gradient-Boosted Trees
May 18, 2026Aditya Tanna, Nassim Bouarour, Mohamed Bouadi +2Tabular Foundation Models Gradient Boosted Tree
Cracks in the Foundation: A Civil Infrastructure Dataset to Challenge Vision Foundation Models
May 18, 2026Nicola Farronato, Niccolo Avogaro, Thomas Frick +6Structural Health Monitoring Wireless Foundation Models
SAFE-SVD: Sensitivity-Aware Fidelity-Enforcing SVD for Physics Foundation Models
May 18, 2026Chengjie Hong, Feixiang He, Yiheng Zeng +2Wireless Foundation Models Learned Image Compression
Guard: Scalable Straggler Detection and Node Health Management for Large-Scale Training
May 18, 2026Guanliang Liu, Abhinandan Patni, Congzhu Lin +14Single Graphics Processing Unit Wireless Foundation Models
AURORA: Contextual Orthogonalization for Geometric Representation Learning in Healthcare Foundation Models
May 18, 2026Yuanyun Zhang, Shi LiElectronic Health Record Foundation Models Representation Learning
Beyond Accuracy: Robustness, Interpretability and Expressiveness of EEG Foundation Models
May 17, 2026Urban Širca, Maryam Alimardani, Stefanos Zafeiriou +1Electroencephalography Foundation Models Wireless Foundation Models
Towards Foundation Models for Relational Databases with Language Models and Graph Neural Networks
May 15, 2026Jingcheng Wu, Ratan Bahadur Thapa, Mojtaba Nayyeri +4Relational Deep Learning Relational
MIND: Decoupling Model-Induced Label Noise via Latent Manifold Disentanglement
May 15, 2026Dayong RenNoisy Labels Wireless Foundation Models
CHoE: Cross-Domain Heterogeneous Graph Prompt Learning via Structure-Conditioned Experts
May 15, 2026Peiyuan Li, Yongqi Huang, Jitao Zhao +3Graph Foundation Model Mixture-of-Experts Models
Agentic Discovery of Neural Architectures: AIRA-Compose and AIRA-Design
May 15, 2026Alberto Pepe, Chien-Yu Lin, Despoina Magka +5Neural Architecture Search Neural Architectures
Protocol-Aware Tokenization and Architecture Co-Design for Wireless Packet Foundation Models
May 14, 2026Swadhin Pradhan, Shazal Irshad, Jerome HenryWireless Foundation Models Generative Pretrained Transformers
Controllable Molecular Generative Foundation Models
May 14, 2026Yihan Zhu, Yuhan Liu, Weijiang Li +2Molecular Generation Generative Models
Eradicating Negative Transfer in Multi-Physics Foundation Models via Sparse Mixture-of-Experts Routing
May 14, 2026Ellwil Sharma, Arastu SharmaFluid Dynamics Mixture-of-Experts Models
NeuroAtlas: Benchmarking Foundation Models for Clinical EEG and Brain-Computer Interfaces
May 14, 2026Konstantinos Kontras, Trui Osselaer, Stylianos G. Mouslech +12Electroencephalography Foundation Models Brain-Computer Interface
CSI-JEPA: Towards Foundation Representations for Ubiquitous Sensing with Minimal Supervision
May 13, 2026Xuanhao Luo, Zhizhen Li, Yuchen LiuChannel State Information Self-Supervised Representations
Mini-JEPA Foundation Model Fleet Enables Agentic Hydrologic Intelligence
May 13, 2026Mashrekur RahmanGeospatial Foundation Models Fundamental Hydrological Principles
TabPFN-3: Technical Report
May 13, 2026Léo Grinsztajn, Klemens Flöge, Oscar Key +38Tabpfn Benchmark Datasets
Mechanistic Interpretability of EEG Foundation Models via Sparse Autoencoders
May 13, 2026William Lehn-Schiøler, Magnus Ruud Kjær, Rahul Thapa +10Electroencephalography Foundation Models Mechanistic Interpretability
Compact Latent Manifold Translation: A Parameter-Efficient Foundation Model for Cross-Modal and Cross-Frequency Physiological Signal Synthesis
May 13, 2026Bo Cui, Xiaowen Song, Yaowen Zhang +4Electronic Health Record Foundation Models Wireless Foundation Models
LoREnc: Low-Rank Encryption for Securing Foundation Models and LoRA Adapters
May 13, 2026Beomjin Ahn, Jungmin Kwon, Chanyong Jung +1Low-Rank Adaptation Adapters Wireless Foundation Models
What Do EEG Foundation Models Capture from Human Brain Signals?
May 12, 2026Ling Tang, Qian Chen, Jilin Mei +6Electroencephalography Foundation Models Electroencephalography Spatial Super-Resolution
CLEF: EEG Foundation Model for Learning Clinical Semantics
May 11, 2026Peng Cao, Ali Mirzazadeh, Jong Woo Lee +2Electroencephalography Foundation Models Electronic Health Record Foundation Models
BatchWeave: A Consistent Object-Store-Native Data Plane for Large Foundation Model Training
May 11, 2026Ting Sun, Junjie Zhang, Xiao Yan +7Well-Tuned Static Batching Policy Weave
Learning Graph Foundation Models on Riemannian Graph-of-Graphs
May 11, 2026Haokun Liu, Zezhong Ding, Xike XieGraph Foundation Model Graph Representations
When More Parameters Hurt: Foundation Model Priors Amplify Worst-Client Disparity Under Extreme Federated Heterogeneity
May 9, 2026Kiran Naseer, Umar ShoaibFederated Learning Fairness-Aware Learning
Compact SO(3) Equivariant Atomistic Foundation Models via Structural Pruning
May 9, 2026Chen Wang, Siyu Hu, Guangming Tan +1Equivariant Neural Networks Wireless Foundation Models
Toward Privileged Foundation Models:LUPI for Accelerated and Improved Learning
May 8, 2026Xueying Ding, Leman AkogluTabular Foundation Models Wireless Foundation Models
Benchmarking Foundation Models for Renal Lesion Stratification in CT
May 8, 2026Hartmut Häntze, Sarah de Boer, Myrthe Buser +7Radiomics Electronic Health Record Foundation Models

May 29, 2026 · cs.LGJ/K move · Enter open · S save

InfoAtlas: A Foundation Model for Zero-Shot Statistical Dependence Estimate

Zhengyang Hu, Yanzhi Chen, Hanxiang Ren, Qunsong Zeng+4

Measuring statistical dependency between high-dimensional random variables is a fundamental task in data science and machine learning. Neural mutual information (MI) estimators offer a promising avenue, but they typically require costly iterative optimization for each new dataset, making them impractical for real-time applications. We present InfoAtlas, a foundation model-like architecture that eliminates this bottleneck by directly inferring MI in a single forward pass. Pretrained on large-scale synthetic data with rich dependence patterns, InfoAtlas learns to identify diverse dependence structures and predict MI directly from the dataset. Comprehensive experiments demonstrate that InfoAtlas matches state-of-the-art neural estimators in accuracy while achieving

100\times

speedup, can flexibly handle varying dimensions and sample sizes through a single unified model, and generalizes effectively to complex, real-world scenarios. By reformulating MI estimation as an inference task, InfoAtlas establishes a foundation for real-time dependency analysis.

Mutual Information Temporal Dependence Machine Learning Wireless Foundation Models Foundation Model Atlas Zero-Shot Benchmark

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