Ax Guifeng Deng, Pan Wang, Jiquan Wang, Shuying Rao, Junyi Xie, Wanjun Guo, Tao Li, Haiteng Jiang 4/1/2026

SleepVLM: Explainable and Rule-Grounded Sleep Staging via a Vision-Language Model

Vision-language model for sleep staging from polysomnography waveforms generating AASM-compliant clinical rationales with auditable reasoning.

Ax Lorcan McLaren, James Cross, Zuzanna Krakowska, Robin Rauner, Martijn Schoonvelde 4/1/2026

Magic Words or Methodical Work? Challenging Conventional Wisdom in LLM-Based Political Text Annotation

Controlled evaluation of how LLM model choice, size, and prompting strategies affect political text annotation, challenging conventional wisdom.

Ax Tanvir Hossain, Muhammad Ifte Khairul Islam, Lilia Chebbah, Charles Fanning, Esra Akbas 4/1/2026

Cross-attentive Cohesive Subgraph Embedding to Mitigate Oversquashing in GNNs

GNN technique using cross-attention and cohesive subgraph embedding to address oversquashing problem in graph neural networks.

Ax Edward J. Yoon 4/1/2026

ITQ3_S: High-Fidelity 3-bit LLM Inference via Interleaved Ternary Quantization with Rotation-Domain Smoothing

3-bit weight quantization method for LLMs using rotation-domain smoothing via Fast Walsh-Hadamard Transform, improving precision in extreme quantization.

Ax Koki Maeda, Naoaki Okazaki 4/1/2026

JaWildText: A Benchmark for Vision-Language Models on Japanese Scene Text Understanding

Benchmark dataset for evaluating vision-language models on Japanese scene text understanding, addressing multilingual complexity challenges.

Ax Chang Zong, Sicheng Lv, Si-tu Xue, Huilin Zheng, Jian Wan, Lei Zhang 4/1/2026

Building evidence-based knowledge graphs from full-text literature for disease-specific biomedical reasoning

EvidenceNet framework uses LLM-assisted pipeline to extract structured, evidence-grounded biomedical findings from full-text literature into knowledge graphs.

Ax Xuan Deng, Xiandong Meng, Hengyu Man, Qiang Zhu, Tiange Zhang, Debin Zhao, Xiaopeng Fan 4/1/2026

LG-HCC: Local Geometry-Aware Hierarchical Context Compression for 3D Gaussian Splatting

Compression technique for 3D Gaussian Splatting using geometry-aware hierarchical context models to reduce storage overhead.

Ax Huanxuan Liao, Zhongtao Jiang, Yupu Hao, Yuqiao Tan, Shizhu He, Ben Wang, Jun Zhao, Kun Xu, Kang Liu 4/1/2026

ResAdapt: Adaptive Resolution for Efficient Multimodal Reasoning

Adaptive resolution framework for multimodal LLMs that reduces visual token overhead through input-side compression before encoding.

Ax Hagen Holthusen, Paul Steinmann, Ellen Kuhl 4/1/2026

A Convex Route to Thermomechanics: Learning Internal Energy and Dissipation

Physics-informed neural network framework for discovering constitutive models in thermomechanics using internal energy and dissipation potentials.

Ax Yuma Ichikawa, Keiji Kimura, Akihiro Yoshida, Yudai Fujimoto, Hiroki Tokura, Yamato Arai, Yoshiyuki Ishii, Yusei Kawakami, Genki Shikada, Achille Jacquemond, Yoshihiko Fujisawa, Katsuki Fujisawa, Takumi Honda, Akira Sakai 4/1/2026

OneComp: One-Line Revolution for Generative AI Model Compression

Framework for post-training compression of generative AI models with single-line implementation, addressing quantization and calibration challenges.

Ax Oktay Karaku\c{s}, Hasan Arkada\c{s} 4/1/2026

Structural Pass Analysis in Football: Learning Pass Archetypes and Tactical Impact from Spatio-Temporal Tracking Data

Analyzes football passes using spatio-temporal tracking data to understand tactical organization and defensive impact.

Ax Ivan Pasichnyk 4/1/2026

Beta-Scheduling: Momentum from Critical Damping as a Diagnostic and Correction Tool for Neural Network Training

Derives time-varying momentum schedule for neural network training from physics principles, eliminating need for manual tuning.

Ax Hassan Ugail, Newton Howard 4/1/2026

A Neural Tension Operator for Curve Subdivision across Constant Curvature Geometries

Neural network learns tension parameters for curve subdivision across different geometries, replacing global parameter with per-edge predictions.

Ax Giovanni Guasti 4/1/2026

Foundations of Polar Linear Algebra

Operator learning framework combining linear radial and periodic angular components through polar geometry.

Ax Chihan Huang, Huaijin Wang, Shuai Wang 4/1/2026

\texttt{ReproMIA}: A Comprehensive Analysis of Model Reprogramming for Proactive Membership Inference Attacks

Privacy attack analysis of model reprogramming for membership inference against deep learning models.

Ax Mingju Liu, Jiaqi Yin, Alvaro Velasquez, Cunxi Yu 4/1/2026

Differentiable Initialization-Accelerated CPU-GPU Hybrid Combinatorial Scheduling

Hybrid CPU-GPU framework combining differentiable optimization with ILP solving for combinatorial scheduling.

Ax Andrea Carbonati, Mohammadsina Almasi, Hadis Anahideh 4/1/2026

Multi-Agent LLMs for Adaptive Acquisition in Bayesian Optimization

Multi-agent LLM framework for Bayesian optimization exploring exploration-exploitation trade-off through implicit reasoning.

Ax Yongzhong Xu 4/1/2026

The Spectral Edge Thesis: A Mathematical Framework for Intra-Signal Phase Transitions in Neural Network Training

Spectral analysis of neural network training phase transitions through rolling-window Gram matrix spectral gap.

Ax Elham Rostami, Taous-Meriem Laleg-Kirati, Hamidou Tembine 4/1/2026

An Explicit Surrogate for Gaussian Mixture Flow Matching with Wasserstein Gap Bounds

Training-free flow matching between Gaussian mixture models with explicit velocity fields and Wasserstein bounds.

Ax Siva Kumar Sastry Hari, Vignesh Balaji, Sana Damani, Qijing Huang, Christos Kozyrakis 4/1/2026

Improving Efficiency of GPU Kernel Optimization Agents using a Domain-Specific Language and Speed-of-Light Guidance

LLM agents for GPU kernel optimization using domain-specific language and speed-of-light guidance to reduce design space.

Ax Abhinna Sundar Samantaray, Finnja Annika Fluhrer, Dhruv Saini, Omkar Charaple, Anish Kumar Singh, Dhruv Vansraj Rathore 4/1/2026

From Astronomy to Astrology: Testing the Illusion of Zodiac-Based Personality Prediction with Machine Learning

ML investigation of zodiac-based personality prediction, testing astrology claims empirically.

Ax Iness Halimi, Emmanuel Piffo, Oumnia Boudersa, Yvan Marcel Carre Vilmorin, Melissa Ait-ikhlef, Karima Kone, Andy Tan, Augustin Medina, Juliette Hernando, Sheila Ernest, Vatche Bartekian, Karine Lalonde, Mireille E Schnitzer, Gianolli Dorcelus 4/1/2026

A Latent Risk-Aware Machine Learning Approach for Predicting Operational Success in Clinical Trials based on TrialsBank

Hierarchical latent risk model for predicting clinical trial success using operational data from trial design phase.

Ax Tushar Dhananjay Pathak 4/1/2026

ARCS: Autoregressive Circuit Synthesis with Topology-Aware Graph Attention and Spec Conditioning

Amortized analog circuit generation system combining graph VAE and flow-matching models with SPICE validation.

Ax Zichao Wei 4/1/2026

On the Mirage of Long-Range Dependency, with an Application to Integer Multiplication

Analysis of long-range dependency in integer multiplication for neural networks through computational spacetime perspective.

Ax Lucas Riera Abbade, Anna Helena Reali Costa 4/1/2026

Realistic Market Impact Modeling for Reinforcement Learning Trading Environments

Gymnasium-compatible RL trading environments with realistic nonlinear market impact models for agent evaluation.

Ax Jaber Jaber, Osama Jaber 4/1/2026

HCLSM: Hierarchical Causal Latent State Machines for Object-Centric World Modeling

Hierarchical world model with object-centric decomposition and causal latent dynamics for video prediction.

Ax Disen Liao, Felix Dangel, Yaoliang Yu 4/1/2026

Efficient Bilevel Optimization with KFAC-Based Hypergradients

Bilevel optimization using KFAC-based hypergradients for efficient inverse Hessian-vector product computation.

Ax Jawad Chowdhury, Ganesh Narasimha, Jan-Chi Yang, Yongtao Liu, Rama Vasudevan 4/1/2026

Quality-Controlled Active Learning via Gaussian Processes for Robust Structure-Property Learning in Autonomous Microscopy

Active learning with Gaussian processes for autonomous microscopy to improve data quality in structure-property learning.

Ax Guan Wang, Shuyin Xia, Lei Qian, Guoyin Wang, Yi Liu, Yi Wang, Wei Wang 4/1/2026

Efficient and Scalable Granular-ball Graph Coarsening Method for Large-scale Graph Node Classification

Graph coarsening method for scalable Graph Convolutional Networks on large-scale node classification tasks.

Ax Yunrui Yu, Xuxiang Feng, Pengda Qin, Pengyang Wang, Kafeng Wang, Cheng-zhong Xu, Hang Su, Jun Zhu 4/1/2026

Dummy-Aware Weighted Attack (DAWA): Breaking the Safe Sink in Dummy Class Defenses

Attack method exposing vulnerabilities in dummy class-based adversarial defenses through weighted attack strategies.

Ax Anci Lin, Xiaohong Liu, Zhiwen Zhang, Weidong Zhao, Wenju Zhao 4/1/2026

Biomimetic PINNs for Cell-Induced Phase Transitions: UQ-R3 Sampling with Causal Gating

Physics-informed neural networks for modeling cell-induced phase transitions with causal gating mechanisms.

Ax Zhangyong Liang 4/1/2026

Stochastic Dimension Implicit Functional Projections for Exact Integral Conservation in High-Dimensional PINNs

Method enforcing exact conservation laws in high-dimensional physics-informed neural networks using stochastic dimension implicit projections.

Ax Lakshya Garg, Sai Yaswanth, Deep Narayan Mishra, Karthik Kumaran, Anupriya Sharma, Mayank Uniyal 4/1/2026

Monodense Deep Neural Model for Determining Item Price Elasticity

Deep neural model predicting item price elasticity for revenue management from historical sales and pricing data.

Ax Shafayeth Jamil, Rehan Kapadia 4/1/2026

Lie Generator Networks for Nonlinear Partial Differential Equations

LGN-KM lifts nonlinear PDE dynamics into linear latent space by learning continuous-time Koopman generator decomposition.

Ax Mohamed Gharib, Leonid Popryho, Inna Partin-Vaisband 4/1/2026

From Physics to Surrogate Intelligence: A Unified Electro-Thermo-Optimization Framework for TSV Networks

Surrogate model framework for electro-thermal optimization of through-substrate vias replacing computationally expensive FEM simulations.

Ax Qinye Zhu, Yu Xiang, Jun Zhang, Wenyong Wang 4/1/2026

LGFNet: Local-Global Fusion Network with Fidelity Gap Delta Learning for Multi-Source Aerodynamics

LGFNet fuses CFD, wind tunnel, and flight test data for aerodynamic modeling using local-global fusion with fidelity gap learning.

Ax Christopher Goetze, Tim Schlippe, Daniel Lakey 4/1/2026

Deep Learning-Based Anomaly Detection in Spacecraft Telemetry on Edge Devices

Three deep learning approaches for spacecraft telemetry anomaly detection optimized for edge device deployment using neural architecture search.

Ax Kaustubh Kartikey, Shalabh Bhatnagar 4/1/2026

Finite-time analysis of Multi-timescale Stochastic Optimization Algorithms

Theoretical finite-time convergence analysis of multi-timescale stochastic optimization algorithms for simulation-based optimization.

Ax Yuxuan Liu, Wenchao Xu, Haozhao Wang, Zhiming He, Zhaofeng Shi, Chongyang Xu, Peichao Wang, Boyuan Zhang 4/1/2026

Causality-inspired Federated Learning for Dynamic Spatio-Temporal Graphs

Federated learning method for graph neural networks on dynamic spatio-temporal graphs addressing heterogeneity across decentralized clients.

Ax Fu Wang, Qifeng Lu, Xinyu Long, Meng Zhang, Xiaofei Yang, Weijia Cao, Xiaowen Chu 4/1/2026

Hybrid Quantum-Classical Spatiotemporal Forecasting for 3D Cloud Fields

Hybrid quantum-classical method for 3D cloud field forecasting using spatiotemporal prediction models for weather analysis.

Ax Zhongheng Jiang, Yuechao Zhao, Donglin Xie, Chenxi Sun, Rongchen Lu, Silu Luo, Zisheng Liang, Shenda Hong 4/1/2026

mtslearn: Machine Learning in Python for Medical Time Series

Open-source Python library for machine learning on medical time-series data, addressing heterogeneous clinical data and reducing friction for ML practitioners in healthcare applications.

Ax Nils Gr\"unefeld, Jes Frellsen, Christian Hardmeier 4/1/2026

An Isotropic Approach to Efficient Uncertainty Quantification with Gradient Norms

Lightweight uncertainty quantification for neural networks using gradient norms and isotropy assumption without training data access.

Ax Dmitrii Seletkov, Paul Hager, Rickmer Braren, Daniel Rueckert, Raphael Rehms 4/1/2026

Survival In-Context: Prior-fitted In-context Learning Tabular Foundation Model for Survival Analysis

Prior-fitted tabular foundation model using in-context learning for survival analysis with limited and censored data.

Ax Beatrix M. G. Nielsen 4/1/2026

Why not to use Cosine Similarity between Label Representations

Analysis showing cosine similarity between label representations in softmax classifiers does not reliably indicate model behavior.

Ax Leonard S. Pleiss, James Harrison, Maximilian Schiffer 4/1/2026

Target-Aligned Reinforcement Learning

Target-Aligned RL (TARL) framework addressing stability-recency tradeoff in target networks through selective emphasis of aligned transitions.

Ax Martin V\'yboh, Gabriela Grmanov\'a 4/1/2026

Capturing Multivariate Dependencies of EV Charging Events: From Parametric Copulas to Neural Density Estimation

Vine copulas and neural density estimation for modeling multivariate dependencies in EV charging event data.

Ax Yacoub Hendi, Daniel Persson, Magdalena Larfors 4/1/2026

The Geometry of Polynomial Group Convolutional Neural Networks

Mathematical framework for polynomial group convolutional neural networks using graded group algebras and neuromanifold analysis.

Ax Cheng Yang, Yu Hao, Qi Zhang, Chuan Shi 4/1/2026

Disentangled Graph Prompting for Out-Of-Distribution Detection

Graph prompt-based method for out-of-distribution detection in neural networks using disentangled representations.

Ax Lixin Xiu, Xufang Luo, Hideki Nakayama 4/1/2026

A Comprehensive Information-Decomposition Analysis of Large Vision-Language Models

Information decomposition framework measuring information spectrum in vision-language models to assess multimodal fusion vs unimodal priors.

Ax Dustin Eisenhardt, Yunhee Jeong, Florian Buettner 4/1/2026

Mind the Gap: A Framework for Assessing Pitfalls in Multimodal Active Learning

Framework analyzing pitfalls in active learning for multimodal data, addressing missing modalities and varying interaction structures.