Ax Hadi Hojjati, Christopher Roth, Rory Woods, Ken Sills, Narges Armanfard 3/30/2026

EngineAD: A Real-World Vehicle Engine Anomaly Detection Dataset

EngineAD real-world multivariate anomaly detection dataset from vehicle fleet sensor telemetry with expert annotations for safety-critical domain.

Ax Hadi Hojjati, Narges Armanfard 3/30/2026

Adversarial-Robust Multivariate Time-Series Anomaly Detection via Joint Information Retention

ARTA joint training framework for adversarially robust multivariate time-series anomaly detection using min-max optimization and information retention.

Ax Renato Cordeiro de Amorim, Vladimir Makarenkov 3/30/2026

On the Objective and Feature Weights of Minkowski Weighted k-Means

Theoretical analysis of Minkowski weighted k-means revealing objective as power-mean aggregation of within-cluster dispersions controlled by exponent.

Ax Mikalai Korbit, Mario Zanon 3/30/2026

Second-Order, First-Class: A Composable Stack for Curvature-Aware Training

Somax composable Optax-native stack for second-order curvature-aware training with modular APIs for operators, estimators, and preconditioners.

Ax Siqiao Xue, Zhaoyang Zhu, Wei Zhang, Rongyao Cai, Rui Wang, Yixiang Mu, Fan Zhou, Jianguo Li, Peng Di, Hang Yu 3/30/2026

QuitoBench: A High-Quality Open Time Series Forecasting Benchmark

QuitoBench open benchmark for time series forecasting covering eight trend-seasonality-forecastability regimes with regime-balanced dataset design.

Ax Linzheng Wang, Jason Chen, Nicolas Tricard, Zituo Chen, Sili Deng 3/30/2026

GLU: Global-Local-Uncertainty Fusion for Scalable Spatiotemporal Reconstruction and Forecasting

GLU framework for sparse spatiotemporal reconstruction and forecasting using global-local-uncertainty fusion with unified state representation.

Ax Alex Glushkovsky 3/30/2026

Identification of Bivariate Causal Directionality Based on Anticipated Asymmetric Geometries

Two methods for identifying causal directionality in bivariate data using anticipated asymmetric geometries and monotonicity measures.

Ax Zhangyong Liang, Huanhuan Gao 3/30/2026

Constitutive parameterized deep energy method for solid mechanics problems with random material parameters

Deep energy method for solid mechanics simulations handling random material parameters without repeated mesh discretization.

Ax Eric Yocam, Varghese Vaidyan, Yong Wang 3/30/2026

H-Node Attack and Defense in Large Language Models

H-Node ANC mechanistic framework identifies and defends hallucination representations in transformer LLMs at individual hidden-state dimensions.

Ax Zhuoyu Cheng, Kohei Hatano, Eiji Takimoto 3/30/2026

Adversarial Bandit Optimization with Globally Bounded Perturbations to Linear Losses

Adversarial bandit optimization framework for non-convex non-smooth loss functions with globally bounded perturbations on linear components.

Ax Christopher Ackerman 3/30/2026

Selective Deficits in LLM Mental Self-Modeling in a Behavior-Based Test of Theory of Mind

Study of LLMs' theory of mind capabilities using behavior-based testing to assess their ability to self-model and model other agents.

Ax Yulun Wu, Sravan Kumar Ankireddy, Samuel Sharpe, Nikita Seleznev, Dehao Yuan, Hyeji Kim, Nam H. Nguyen 3/30/2026

Dynamic Tokenization via Reinforcement Patching: End-to-end Training and Zero-shot Transfer

Dynamic Tokenization via Reinforcement Patching learns variable-sized data-driven patches for long-horizon sequence models with zero-shot transfer capability.

Ax Yuhang Ma, Jie Wang, Zheng Yan 3/30/2026

Are LLM-Enhanced Graph Neural Networks Robust against Poisoning Attacks?

Framework assessing robustness of LLM-enhanced Graph Neural Networks against poisoning attacks targeting both graph structure and textual attributes.

Ax Shuangliang Li, Siwei Li, Li Li, Weijie Zou, Jie Yang, Maolin Zhang 3/30/2026

Accurate Precipitation Forecast by Efficiently Learning from Massive Atmospheric Variables and Unbalanced Distribution

Deep learning approach for short-term precipitation forecasting handling massive atmospheric variables and class imbalance in weather data.

Ax Magnus H. Str{\o}mme, Alex G. C. de S\'a, David B. Ascher 3/30/2026

DPD-Cancer: Explainable Graph-based Deep Learning for Small Molecule Anti-Cancer Activity Prediction

DPD-Cancer uses graph-based deep learning for predicting anti-cancer drug activity and molecular structure-cellular interaction modeling.

Ax Amar Almaini, Jakob Folz, Ghadeer Ashour 3/30/2026

TinyML for Acoustic Anomaly Detection in IoT Sensor Networks

TinyML pipeline for real-time acoustic anomaly detection on IoT microcontrollers for environmental sound monitoring without cloud processing.

Ax Bhavya Kohli, Biplab Sikdar 3/30/2026

PEANUT: Perturbations by Eigenvalue Alignment for Attacking GNNs Under Topology-Driven Message Passing

PEANUT proposes perturbation-based adversarial attack method targeting robustness vulnerabilities in Graph Neural Networks through topology modifications.

Ax Humaira Kousar, Hasnain Irshad Bhatti, Jaekyun Moon 3/30/2026

PruneFuse: Efficient Data Selection via Weight Pruning and Network Fusion

PruneFuse strategy uses pruned networks for efficient data selection and fuses them with original networks to optimize deep neural network training.

Ax Mostafa Haghir Chehreghani 3/30/2026

On the Complexity of Optimal Graph Rewiring for Oversmoothing and Oversquashing in Graph Neural Networks

Complexity analysis of optimal graph rewiring to address oversmoothing and oversquashing in deep graph neural networks.

Ax Hao Liang, Zhengyang Zhao, Meiyi Qiang, Mingrui Chen, Lu Ma, Rongyi Yu, Hengyi Feng, Shixuan Sun, Zimo Meng, Xiaochen Ma, Xuanlin Yang, Qifeng Cai, Ruichuan An, Bohan Zeng, Zhen Hao Wong, Chengyu Shen, Runming He, Zhaoyang Han, Yaowei Zheng, Fangcheng Fu, Conghui He, Bin Cui, Zhiyu Li, Weinan E, Wentao Zhang 3/30/2026

DataFlex: A Unified Framework for Data-Centric Dynamic Training of Large Language Models

Unified framework for data-centric dynamic training of LLMs with consistent interfaces for data selection and reweighting.

Ax Gilles Wainrib, Barbara Bodinier, Haitem Dakhli, Josep Monserrat, Almudena Espin Perez, Sabrina Carpentier, Roberta Codato, John Klein 3/30/2026

Can AI Scientist Agents Learn from Lab-in-the-Loop Feedback? Evidence from Iterative Perturbation Discovery

Study of LLM-based AI scientist agents learning from iterative experimental feedback in cell screening with 800 replicated experiments.

Ax Jicheng Ma, Yunyan Yang, Juan Zhao, Liang Zhao 3/30/2026

Geometric Evolution Graph Convolutional Networks: Enhancing Graph Representation Learning via Ricci Flow

Graph neural network framework using Ricci flow for improved geometric representation learning on graphs.

Ax Abdelkrim Alahyane (LAAS-SARA), C\'eline Comte (CNRS, LAAS-SARA), Matthieu Jonckheere (CNRS, LAAS-SARA) 3/30/2026

Optimization Trade-offs in Asynchronous Federated Learning: A Stochastic Networks Approach

Analysis of optimization trade-offs in asynchronous federated learning addressing gradient staleness and client bias.

Ax Pascal Henrich, Jonas Sievers, Maximilian Beichter, Thomas Blank, Ralf Mikut, Veit Hagenmeyer 3/30/2026

Knowledge Distillation for Efficient Transformer-Based Reinforcement Learning in Hardware-Constrained Energy Management Systems

Knowledge distillation approach for deploying Transformer-based reinforcement learning on resource-constrained energy management devices.

Ax Marion Taconn\'e, Valentina D. A. Corino, Annamaria Del Franco, Sara Giovani, Iacopo Olivotto, Adrien Al Wazzan, Erwan Donal, Pietro Cerveri, Luca Mainardi 3/30/2026

Improving Risk Stratification in Hypertrophic Cardiomyopathy: A Novel Score Combining Echocardiography, Clinical, and Medication Data

Machine learning risk score for hypertrophic cardiomyopathy combining echocardiography and clinical data.

Ax Yahya Alkhatib, Wee Peng Tay 3/30/2026

Contrastive Conformal Sets

Conformal prediction extension for contrastive learning with learnable multi-norm constraints and coverage guarantees.

Ax Shuyi Gao, Stavros Orfanoudakis, Shengren Hou, Peter Palensky, Pedro P. Vergara 3/30/2026

Topology-Aware Graph Reinforcement Learning for Energy Storage Systems Optimal Dispatch in Distribution Networks

Topology-aware reinforcement learning with GNNs for optimal dispatch of energy storage systems in distribution networks.

Ax Qurat Ul Ain, Alptekin Temizel, Soyiba Jawed 3/30/2026

D-GATNet: Interpretable Temporal Graph Attention Learning for ADHD Identification Using Dynamic Functional Connectivity

Graph attention network for ADHD identification using dynamic functional connectivity from fMRI data.

Ax Ajith Anil Meera, Wouter Kouw 3/30/2026

Curvature-aware Expected Free Energy as an Acquisition Function for Bayesian Optimization

Expected free energy acquisition function for Bayesian optimization with convergence guarantees and connections to existing methods.

Ax Steffen Herbold, Florian Lemmerich 3/30/2026

A Formal Framework for Uncertainty Analysis of Text Generation with Large Language Models

Formal framework for measuring uncertainty in LLM text generation accounting for prompting, generation, and interpretation stages.

Ax Senura Hansaja Wanasekara, Minh-Duong Nguyen, Xiaochen Liu, Nguyen H. Tran, Ken-Tye Yong 3/30/2026

Generative Modeling in Protein Design: Neural Representations, Conditional Generation, and Evaluation Standards

Survey of generative modeling in protein design covering neural representations, conditional generation, and evaluation standards.

Ax Roberto Sprengel Minozzo Tomchak, Oge Marques, Lucas Garcia Pedroso, Luiz Eduardo Oliveira, Paulo Lisboa de Almeida 3/30/2026

Maintaining Difficulty: A Margin Scheduler for Triplet Loss in Siamese Networks Training

Margin scheduler for triplet loss in Siamese networks to improve distance metric learning training dynamics.

Ax Siddhartha Laghuvarapu, Rohan Deb, Jimeng Sun 3/30/2026

KMM-CP: Practical Conformal Prediction under Covariate Shift via Selective Kernel Mean Matching

Conformal prediction method for uncertainty quantification under covariate shift using selective kernel mean matching.

Ax Yue Li, Shujuan Chen, Akihiro Shimoda, Ying Jin 3/30/2026

Interpretable long-term traffic modelling on national road networks using theory-informed deep learning

Theory-informed deep learning model for long-term traffic forecasting balancing interpretability and predictive accuracy.

Ax Devashish Gaikwad, Wil M. P. van der Aalst, Gyunam Park 3/30/2026

Neuro-Symbolic Process Anomaly Detection

Neuro-symbolic approach combining neural networks and domain knowledge for process anomaly detection from event logs.

Ax Christian Mugisho Zagabe, Sebastian Petiz 3/30/2026

Automatic feature identification in least-squares policy iteration using the Koopman operator framework

Koopman autoencoder-based least-squares policy iteration algorithm enabling automatic feature learning in reinforcement learning.

Ax Zhixuan Cao, Yishu Xu, Xuang WU 3/30/2026

A Boltzmann-machine-enhanced Transformer For DNA Sequence Classification

Transformer enhanced with Boltzmann machines for DNA sequence classification to uncover latent interactions and higher-order dependencies.

Ax Fadoua Amri-Jouidel, Emmanuel Kemel, St\'ephane Mussard 3/30/2026

Shapley meets Rawls: an integrated framework for measuring and explaining unfairness

Framework using Shapley values to measure and explain unfairness in machine learning models under group fairness criteria with inference methods.

Ax Deepika Gurung, Lala Shakti Swarup Ray, Mengxi Liu, Bo Zhou, Paul Lukowicz 3/30/2026

SPECTRA: An Efficient Spectral-Informed Neural Network for Sensor-Based Activity Recognition

SPECTRA: spectral-informed neural network for sensor-based activity recognition optimized for edge deployment with low latency and privacy.

Ax Mostafa Anoosha, Dhavalkumar Thakker, Kuniko Paxton, Koorosh Aslansefat, Bhupesh Kumar Mishra, Baseer Ahmad, Rameez Raja Kureshi 3/30/2026

EcoFair: Trustworthy and Energy-Aware Routing for Privacy-Preserving Vertically Partitioned Medical Inference

EcoFair: privacy-preserving medical inference framework with lightweight routing for vertically partitioned data and modality-specific embeddings.

Ax Juno Kim, Eshaan Nichani, Denny Wu, Alberto Bietti, Jason D. Lee 3/30/2026

Sharp Capacity Scaling of Spectral Optimizers in Learning Associative Memory

Theoretical analysis of spectral optimizers like Muon in language model training, studying capacity scaling through linear associative memory framework.

Ax Jingpu Cheng, Ping Liu, Qianxiao Li, Chi Zhang 3/30/2026

Machine Unlearning under Retain-Forget Entanglement

Machine unlearning framework addressing retain-forget entanglement where retained samples unintentionally affected by forgetting correlated features.

Ax Matthias Boeker, Dana Swarbrick, Ulysse T. A. C\^ot\'e-Allard, Marc T. P. Adam, Hugo L. Hammer, P{\aa}l Halvorsen 3/30/2026

The Climber's Grip -- Personalized Deep Learning Models for Fear and Muscle Activity in Climbing

Deep learning models for fear and muscle activity correlation in climbing sports using psychophysiological data. Niche domain application.

Ax Einari Vaaras, Manu Airaksinen, Okko R\"as\"anen 3/30/2026

Evaluating Interactive 2D Visualization as a Sample Selection Strategy for Biomedical Time-Series Data Annotation

Study comparing sample selection methods (random, farthest-first, interactive visualization) for annotation of biomedical time-series data with real annotators.

Ax Roope Niemi, Anastasiia Petrovych, Arghya Ranjan Das, Enrico Lupi, Chang Sun, Dimitrios Danopoulos, Marlon Joshua Helbing, Mia Liu, Sebastian Dittmeier, Michael Kagan, Vladimir Loncar, Maurizio Pierini 3/30/2026

PQuantML: A Tool for End-to-End Hardware-aware Model Compression

PQuantML: open-source hardware-aware neural network compression library for pruning and quantization with unified interface for latency-constrained deployment.

Ax Luca Lanzilao, Angela Meyer 3/30/2026

Characterization and forecasting of national-scale solar power ramp events

Machine learning approach to forecasting solar power ramp events for grid stability. Energy domain application.

Ax Sagar Addepalli, Prajita Bhattarai, Abhilasha Dave, Julia Gonski 3/30/2026

Hardware-Aware Tensor Networks for Real-Time Quantum-Inspired Anomaly Detection at Particle Colliders

Quantum-inspired anomaly detection using hardware-aware tensor networks for particle collider physics, deployable on classical hardware.

Ax Rafael Izbicki, Pedro L. C. Rodrigues 3/30/2026

Benchmarking Tabular Foundation Models for Conditional Density Estimation in Regression

Systematic evaluation of tabular foundation models like TabPFN and TabICL for conditional density estimation in regression tasks with heteroscedasticity.

Ax Pranuthi Tenali, Sahil Sidheekh, Saurabh Mathur, Erik Blasch, Kristian Kersting, Sriraam Natarajan 3/30/2026

Context-specific Credibility-aware Multimodal Fusion with Conditional Probabilistic Circuits

C²MF: context-specific credibility-aware multimodal fusion framework using probabilistic circuits to handle conflicting modalities and situational reliability changes.

Ax Toby Lovick, David Yallup, Will Handley 3/30/2026

Automatic Laplace Collapsed Sampling: Scalable Marginalisation of Latent Parameters via Automatic Differentiation

Framework for marginalizing latent parameters in Bayesian models via automatic differentiation combined with nested sampling.