Ax Alaa Zniber, Mounir Ghogho, Ouassim Karrakchou, Mehdi Zakroum 4/1/2026

Early Exiting Predictive Coding Neural Networks for Edge AI

Early exiting predictive coding neural networks optimized for edge AI devices with resource constraints and privacy requirements.

Ax Minhyuk Seo, Seongwon Cho, Minjae Lee, Diganta Misra, Hyeonbeom Choi, Seon Joo Kim, Jonghyun Choi 4/1/2026

GenOL: Generating Diverse Examples for Name-only Online Learning

GenOL framework for online learning with only concept names (name-only setup) enabling real-time adaptation to data distribution shifts in continual learning scenarios.

Ax Tao Han, Zhibin Wen, Zhenghao Chen, Dazhao Du, Song Guo, Lei Bai 4/1/2026

Benchmarking Physics-Informed Time-Series Models for Operational Global Station Weather Forecasting

Introduces WEATHER-5K dataset and benchmarks physics-informed time-series forecasting models for global weather prediction.

Ax Weiqin Chen, Mark S. Squillante, Chai Wah Wu, Santiago Paternain 4/1/2026

A General Control-Theoretic Approach for Reinforcement Learning: Theory and Algorithms

Control-theoretic approach to reinforcement learning with convergence guarantees, new gradient theorem, and gradient ascent algorithm.

Ax Ruida Zhou, Chao Tian, Suhas Diggavi 4/1/2026

An Information-Theoretic Approach to Understanding Transformers' In-Context Learning of Variable-Order Markov Chains

Information-theoretic analysis of transformer in-context learning on variable-order Markov chains with finite-sample accuracy bounds.

Ax Himchan Hwang, Hyeokju Jeong, Dong Kyu Shin, Che-Sang Park, Sehee Kweon, Sangwoong Yoon, Frank Chongwoo Park 4/1/2026

Value Gradient Sampler: Learning Invariant Value Functions for Equivariant Diffusion Sampling

Diffusion sampler using value functions with invariant symmetries for sampling from unnormalized target densities.

Ax Francesco Ballerin, Nello Blaser, Erlend Grong 4/1/2026

SO(3)-Equivariant Neural Networks for Learning from Scalar and Vector Fields on Spheres

Equivariant neural networks for analyzing scalar and vector fields on spheres using group convolutions in Fourier space.

Ax Sy-Tuyen Ho, Koh Jun Hao, Ngoc-Bao Nguyen, Alexander Binder, Ngai-Man Cheung 4/1/2026

Revisiting Model Inversion Evaluation: From Misleading Standards to Reliable Privacy Assessment

Critical evaluation of model inversion attack assessment frameworks, identifying flaws in standard evaluation methodology.

Ax Chaolong Ying, Yingqi Ruan, Xuemin Chen, Yaomin Wang, Tianshu Yu 4/1/2026

Neural Graduated Assignment for Maximum Common Edge Subgraphs

Neural Graduated Assignment method for solving Maximum Common Edge Subgraph problem with improved scalability.

Ax Zehua Pei, Ying Zhang, Hui-Ling Zhen, Tao Yuan, Xianzhi Yu, Zhenhua Dong, Sinno Jialin Pan, Mingxuan Yuan, Bei Yu 4/1/2026

PreMoE: Proactive Inference for Efficient Mixture-of-Experts

Training-free framework for compiling sparse Mixture-of-Experts variants with predicted expert utility metric for deployment optimization.

Ax Ivan Y. Tyukin, Bogdan Grechuk, Evgeny M. Mirkes, Alexander N. Gorban 4/1/2026

When fractional quasi p-norms concentrate

Theoretical analysis of concentration properties for fractional quasi p-norms in high-dimensional spaces.

Ax Sabina J. Sloman, Michele Caprio, Samuel Kaski 4/1/2026

Epistemic Errors of Imperfect Multitask Learners When Distributions Shift

Framework for characterizing epistemic errors in uncertainty-aware multitask learners under distribution shift.

Ax Ziwei Li, Yuhan Duan, Tianyu Xiong, Yi-Tang Chen, Wei-Lun Chao, Han-Wei Shen 4/1/2026

FA-INR: Adaptive Implicit Neural Representations for Interpretable Exploration of Simulation Ensembles

Implicit neural representations for efficient exploration of large-scale simulation ensembles with interpretability focus.

Ax Florian Andreas Marwitz, Ralf M\"oller, Magnus Bender, Marcel Gehrke 4/1/2026

Denoising the Future: Top-p Distributions for Moving Through Time

Probabilistic inference speedup for Hidden Markov Models by filtering low-probability states in temporal sequences.

Ax Johannes Exenberger, Sascha Ranftl, Robert Peharz 4/1/2026

Deep Polynomial Chaos Expansion

Classical polynomial chaos expansion technique for surrogate modeling and uncertainty quantification in physical simulation.

Ax Yining Lu, Zilong Wang, Shiyang Li, Xin Liu, Changlong Yu, Qingyu Yin, Zhan Shi, Zixuan Zhang, Meng Jiang 4/1/2026

Learning to Optimize Multi-Objective Alignment Through Dynamic Reward Weighting

Research on dynamic reward weighting for multi-objective RL alignment in LLMs, addressing non-convex Pareto fronts in preference learning.

Ax Robiul Islam, Dmitry I. Ignatov, Karl Kaberg, Roman Nabatchikov 4/1/2026

Exploring the Relationship between Brain Hemisphere States and Frequency Bands through Classical Machine Learning and Deep Learning Optimization Techniques with Neurofeedback

Comparative study of neural network classifiers and optimizers for EEG frequency band classification across brain hemispheres.

Ax Da Chang, Yongxiang Liu, Ganzhao Yuan 4/1/2026

On the Convergence of Muon and Beyond

Theoretical convergence analysis of Muon optimizer for matrix-structured parameters in neural network training.

Ax M. Giselle Fern\'andez-Godino, Meir H. Shachar, Kevin Korner, Jonathan L. Belof, Mukul Kumar, Jonathan Lind, William J. Schill 4/1/2026

Spatio-temporal, multi-field deep learning of shock propagation in meso-structured media

Deep learning for predicting shock propagation in porous materials with multi-field, spatio-temporal modeling.

Ax Bogdan Raoni\'c, Siddhartha Mishra, Samuel Lanthaler 4/1/2026

Towards a Certificate of Trust: Task-Aware OOD Detection for Scientific AI

Out-of-distribution detection for regression tasks in scientific AI using score-based diffusion models on joint likelihood estimation.

Ax Ahmed A. Elhag, Arun Raja, Alex Morehead, Samuel M. Blau, Hongtao Zhao, Christian Tyrchan, Eva Nittinger, Garrett M. Morris, Michael M. Bronstein 4/1/2026

Learning Inter-Atomic Potentials without Explicit Equivariance

Transformer-based inter-atomic potential model for molecular simulations without explicit equivariance constraints.

Ax Jialin Liu, Lisang Ding, Stanley Osher, Wotao Yin 4/1/2026

Expressive Power of Implicit Models: Rich Equilibria and Test-Time Scaling

Analysis of implicit models with infinite-depth weight-tied networks that match explicit models while reducing memory consumption.

Ax Ali Azizpour, Reza Ramezanpour, Santiago Segarra 4/1/2026

From Moments to Models: Graphon-Mixture Learning for Mixup and Contrastive Learning

Framework for learning graphon mixtures from graph data using motif moments for clustering graphs from multiple distributions.

Ax Arindam Chowdhury, Massimiliano Lupo Pasini 4/1/2026

When Does Global Attention Help? A Unified Empirical Study on Atomistic Graph Learning

Empirical study comparing message passing neural networks and graph transformers for atomistic property prediction.

Ax Penghao Yu, Haotian Jiang, Zeyu Bao, Ruoxi Yu, Qianxiao Li 4/1/2026

The Effect of Attention Head Count on Transformer Approximation

Theoretical analysis of how attention head count influences transformer approximation properties and expressive power.

Ax Jindong Tian, Yifei Ding, Ronghui Xu, Hao Miao, Chenjuan Guo, Bin Yang 4/1/2026

ARROW: An Adaptive Rollout and Routing Method for Global Weather Forecasting

Adaptive rollout and routing method for data-driven weather forecasting with improved spatiotemporal modeling.

Ax Masahiro Negishi, Hyunsoo Park, Kinga O. Mastej, Aron Walsh 4/1/2026

Continuous SUN (Stable, Unique, and Novel) Metric for Generative Modeling of Inorganic Crystals

Novel evaluation metrics for generative models in crystal/material discovery assessing stability, uniqueness, and novelty.

Ax Yubo Zhang, Xiao-Yang Liu, Xiaodong Wang 4/1/2026

A Semi-amortized Lifted Learning-to-Optimize Masked (SALLO-M) Transformer Model for Scalable and Generalizable Beamforming

Learning-to-optimize Transformer framework for scalable beamforming in multi-user wireless systems.

Ax Floris-Jan Willemsen, Niki van Stein, Ben van Werkhoven 4/1/2026

Automated Algorithm Design for Auto-Tuning Optimizers

Automated algorithm design using machine learning to optimize hyperparameter auto-tuning for high-performance applications.

Ax Hyeongkyun Kim, Orestis Oikonomou 4/1/2026

ZeroFlood: Flood Hazard Mapping from Single-Modality SAR Using Geo-Foundation Models

Geo-Foundation Models framework for flood hazard mapping from SAR satellite imagery in data-scarce regions.

Ax Heshan Fernando, Quan Xiao, Parikshit Ram, Yi Zhou, Horst Samulowitz, Nathalie Baracaldo, Tianyi Chen 4/1/2026

Balancing Multi-modal Sensor Learning via Multi-objective Optimization

Multi-objective optimization approach for balancing training dynamics across multiple sensor modalities in learning-enabled control systems.

Ax Gin\'es Carreto Pic\'on, Peng Yuan Zhou, Qi Zhang, Alexandros Iosifidis 4/1/2026

DeepCoT: Deep Continual Transformers for Real-Time Inference on Data Streams

Continual Transformers architecture for real-time low-latency inference on streaming data with reduced redundant computation.

Ax Nir Shlezinger, Santiago Segarra, Yi Zhang, Dvir Avrahami, Zohar Davidov, Tirza Routtenberg, Yonina C. Eldar 4/1/2026

Deep Unfolding: Recent Developments, Theory, and Design Guidelines

Survey of deep unfolding techniques combining classical optimization algorithms with neural networks for signal processing.

Ax Mingzhi Chen, Taiming Lu, Jiachen Zhu, Mingjie Sun, Zhuang Liu 4/1/2026

Stronger Normalization-Free Transformers

Research on normalization-free transformer architectures using Dynamic Tanh as alternative to standard normalization layers.

Ax Allen Liu 4/1/2026

Provably Extracting the Features from a General Superposition

Learning-theoretic approach to extracting interpretable features from superposition in complex ML models.

Ax Iason Kyriakopoulos, Yannis Theodoridis 4/1/2026

Electric Vehicle Charging Load Forecasting: An Experimental Comparison of Machine Learning Methods

Comparative study of ML methods for forecasting electric vehicle charging demand across different time horizons.

Ax Huyen Vo, Isabel Valera 4/1/2026

Hellinger Multimodal Variational Autoencoders

Multimodal VAE method using Hellinger distance and probabilistic opinion pooling for weakly supervised generative learning.

Ax Aakriti Lnu, Zhe Li, Dandan Liang, Chao Huang, Rui Li, Haibo Yang 4/1/2026

HOSL: Hybrid-Order Split Learning for Memory-Constrained Edge Training

Split learning system using hybrid-order optimization to reduce memory overhead for collaborative LLM training on edge devices.

Ax Junichiro Niimi 4/1/2026

The Mouth is Not the Brain: Bridging Energy-Based World Models and Language Generation

Architecture separating energy-based world models from language generation in LLMs to improve understanding vs. fluency tradeoff.

Ax Jiaqi Yin, Baiming Chen, Jia Fei, Mingjun Yang 4/1/2026

PAIR-Former: Budgeted Relational MIL for miRNA Target Prediction

PAIR-Former applies budgeted relational multi-instance learning to miRNA target prediction with compute constraints and instance-level relational processing.

Ax Yuze Wang, Yujia Tong, Xuan Liu, Junhao Dong 4/1/2026

Sparsity-Aware Unlearning for Large Language Models

Addresses machine unlearning for sparse LLMs to remove memorized sensitive information while maintaining model sparsification benefits for efficient deployment.

Ax Jie Xiao, Meng Chen, Qingnan Ren, Jingwei Song, Jiaqi Huang, Yangshen Deng, Chris Tong, Wanyi Chen, Suli Wang, Ziqian Bi, Shuo Lu, Yiqun Duan, Xu Wang, Rymon Yu, Ween Yang, Lynn Ai, Eric Yang, Bill Shi 4/1/2026

ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning

ECHO-2 is distributed RL framework for LLM post-training via reinforcement learning, optimizing cost-efficiency of rollout generation across distributed resources.

Ax Amin Oji, Paul Fieguth 4/1/2026

Joint Embedding Variational Bayes

VJE introduces reconstruction-free latent-variable framework for self-supervised learning using symmetric conditional ELBO on paired embeddings.

Ax Alix Benoit (EMPA), Toni Ivas (EMPA), Mateusz Papierz (Terra Quantum AG), Asel Sagingalieva (Terra Quantum AG), Alexey Melnikov (Terra Quantum AG), Elia Iseli (EMPA) 4/1/2026

A Fast and Generalizable Fourier Neural Operator-Based Surrogate for Melt-Pool Prediction in Laser Processing

LP-FNO uses Fourier Neural Operators as surrogate model for laser welding simulations, enabling faster parametric solution learning for industrial process optimization.

Ax Luca Ghafourpour, Sinho Chewi, Alessio Figalli, Aram-Alexandre Pooladian 4/1/2026

Variational inference via radial transport

Proposes radVI algorithm for variational inference by optimizing radial profiles to better approximate high-dimensional distributions beyond standard Gaussian surrogates.

Ax Aleksei Liuliakov, Luca Hermes, Barbara Hammer 4/1/2026

DGPO: RL-Steered Graph Diffusion for Neural Architecture Generation

DGPO: RL-guided graph diffusion model for neural architecture search using reinforcement learning steering.

Ax Alvaro Paredes Amorin, Andre Python, Christoph Weisser 4/1/2026

Not All News Is Equal: Topic- and Event-Conditional Sentiment from Finetuned LLMs for Aluminum Price Forecasting

Study using finetuned LLMs for topic-conditional sentiment extraction to forecast aluminum commodity prices.

Ax Zakia Zaman, Praveen Gauravaram, Mahbub Hassan, Sanjay Jha, Wen Hu 4/1/2026

Privacy-Preserving Machine Learning for IoT: A Cross-Paradigm Survey and Future Roadmap

Survey of privacy-preserving ML techniques for IoT including federated learning and differential privacy approaches.

Ax Joyjit Roy, Samaresh Kumar Singh, Sushanta Das 4/1/2026

Real-Time Driver Safety Scoring Through Inverse Crash Probability Modeling

SafeDriver-IQ: Framework using inverse crash probability modeling for real-time driver safety scoring.

Ax Mikoto Kudo, Takumi Tanabe, Akifumi Wachi, Youhei Akimoto 4/1/2026

Sample-Efficient Hypergradient Estimation for Decentralized Bi-Level Reinforcement Learning

Decentralized bi-level RL algorithm for environment design with sample-efficient hypergradient estimation.