Ax Hojin Kim, Romit Maulik 4/3/2026

Interpretable Diagnostics and Adaptive Data Assimilation for Neural ODEs via Discrete Empirical Interpolation

Framework using Discrete Empirical Interpolation Method for interpretability in neural ODEs and dynamical system analysis.

Ax Yugong Zeng, Jiayuan Wang, Jonathan Wu 4/3/2026

A Review of Neural Networks in Precipitation Prediction

Review of neural network approaches for precipitation prediction, comparing traditional NWP with deep learning methods.

Ax Yuen Chen, Yulun Wu, Samuel Sharpe, Igor Melnyk, Nam H. Nguyen, Furong Huang, C. Bayan Bruss, Rizal Fathony 4/3/2026

Bridging the Divide: End-to-End Sequence-Graph Learning

Research on jointly learning sequential and relational data for prediction tasks involving entities, integrating sequence and graph modeling.

Ax Weimin Huang, Ryan Piansky, Bistra Dilkina, Daniel K. Molzahn 4/3/2026

Machine Learning Guided Optimal Transmission Switching to Mitigate Wildfire Ignition Risk

ML approach to optimize power line de-energization decisions for wildfire risk mitigation by solving mixed-integer linear programs faster for operational power systems.

Ax Paul Strang, Zacharie Al\`es, C\^ome Bissuel, Olivier Juan, Safia Kedad-Sidhoum, Emmanuel Rachelson 4/3/2026

Planning in Branch-and-Bound: Model-Based Reinforcement Learning for Exact Combinatorial Optimization

Research applying model-based reinforcement learning to improve variable selection heuristics in branch-and-bound solvers for mixed-integer linear programming and combinatorial optimization problems.

Ax YongKyung Oh, Dong-Young Lim, Sungil Kim 4/3/2026

FlowPath: Learning Data-Driven Manifolds with Invertible Flows for Robust Irregularly-sampled Time Series Classification

Invertible flow-based method for learning data-driven manifolds in irregularly-sampled time series classification.

Ax Zhijie Zhong, Zhiwen Yu, Kaixiang Yang, Yongheng Liu, Jun Jiang, C. L. Philip Chen 4/3/2026

Labels Matter More Than Models: Rethinking the Unsupervised Paradigm in Time Series Anomaly Detection

Study on impact of label quality versus model complexity in time series anomaly detection with limited labels.

Ax Shreevanth Krishnaa Gopalakrishnan, Stephen Hailes 4/3/2026

Towards Trustworthy Wi-Fi CSI-based Sensing: Systematic Evaluation of Adversarial Robustness

Adversarial robustness evaluation of CSI-based wireless sensing models for human activity recognition.

Ax Tai Nguyen, Phong Le, Andr\'e Biedenkapp, Carola Doerr, Nguyen Dang 4/3/2026

Deep Reinforcement Learning for Dynamic Algorithm Configuration: A Case Study on Optimizing OneMax with the (1+($\lambda$,$\lambda$))-GA

Deep RL study for dynamic algorithm configuration using DDQN and PPO on evolutionary algorithm parameter control.

Ax Mohammad Arif Rasyidi, Omar Alhussein, Sami Muhaidat, Ernesto Damiani 4/3/2026

Hybrid Quantum-Classical Autoencoders for Unsupervised Network Intrusion Detection

Large-scale evaluation of hybrid quantum-classical autoencoders for unsupervised network intrusion detection.

Ax Yifan Zhang, Zixiang Chen, Yifeng Liu, Zhen Qin, Huizhuo Yuan, Kangping Xu, Yang Yuan, Quanquan Gu, Andrew Chi-Chih Yao 4/3/2026

Group Representational Position Encoding

Unified positional encoding framework using group actions for transformers, unifying rotational and additive approaches.

Ax Lingjing Kong, Shaoan Xie, Guangyi Chen, Yuewen Sun, Xiangchen Song, Eric P. Xing, Kun Zhang 4/3/2026

Beyond the Black Box: Identifiable Interpretation and Control in Generative Models via Causal Minimality

Causal framework for interpretable and controllable generative models with theoretical guarantees.

Ax Felix Stollenwerk, Anna Lokrantz, Niclas Hertzberg 4/3/2026

Output Embedding Centering for Stable LLM Pretraining

Technique addressing output logit divergence instability during LLM pretraining via embedding centering.

Ax Yiyuan Li, Zhen Huang, Yanan Wu, Weixun Wang, Xuefeng Li, Yijia Luo, Wenbo Su, Bo Zheng, Pengfei Liu 4/3/2026

One Sample to Rule Them All: Extreme Data Efficiency in Multidiscipline Reasoning with Reinforcement Learning

One-shot reinforcement learning approach for improving LLM reasoning across multiple domains with minimal data.

Ax Tianrun Yu, Kaixiang Zhao, Cheng Zhang, Anjun Gao, Yueyang Quan, Zhuqing Liu, Minghong Fang 4/3/2026

When the Server Steps In: Calibrated Updates for Fair Federated Learning

Fairness-aware federated learning method with calibrated server updates across demographic groups.

Ax Qingyue Zhang, Chang Chu, Haohao Fu, Tianren Peng, Yanru Wu, Guanbo Huang, Yang Li, Shao-Lun Huang 4/3/2026

Unified Optimization of Source Weights and Transfer Quantities in Multi-Source Transfer Learning: An Asymptotic Framework

Theoretical framework jointly optimizing source weights and transfer quantities in multi-source transfer learning.

Ax Shijun Zhang, Zuowei Shen, Yuesheng Xu 4/3/2026

Multigrade Neural Network Approximation

Multigrade deep learning framework for structured error refinement in neural network training.

Ax Hao Fang, Ryan A. Canfield, Tomohiro Ouchi, Beatrice Macagno, Eli Shlizerman, Amy L. Orsborn 4/3/2026

RPNT: Robust Pre-trained Neural Transformer -- A Pathway for Generalized Motor Decoding

Pre-trained transformer for brain motor decoding that generalizes across recording sites and subjects.

Ax Alejandro Luque-Cerpa, Mengyuan Wang, Emil Carlsson, Sanjit A. Seshia, Devdatt Dubhashi, Hazem Torfah 4/3/2026

Learning Contextual Runtime Monitors for Safe AI-Based Autonomy

Context-aware runtime monitors for safe AI-based autonomous systems using ensemble ML controllers.

Ax Shihao Shao, Cong Fang, Zhouchen Lin, Dacheng Tao 4/3/2026

Partial Feedback Online Learning

Theoretical framework for online learning with partial feedback and collection version spaces.

Ax Anderson de Andrade, Alon Harell, Ivan V. Baji\'c 4/3/2026

Rate-Distortion Optimization for Transformer Inference

Rate-distortion framework for lossy compression of transformer intermediate representations to reduce inference compute and memory.

Ax Zeyuan He, Yupeng Chen, Lang Lin, Yihan Wang, Shenxu Chang, Eric Sommerlade, Philip Torr, Junchi Yu, Adel Bibi, Jialin Yu 4/3/2026

Safer by Diffusion, Broken by Context: Diffusion LLM's Safety Blessing and Its Failure Mode

Analysis of safety properties in diffusion-based LLMs versus autoregressive LLMs, showing robustness against jailbreak attacks.

Ax Jayadev Billa 4/3/2026

The Geometric Anatomy of Capability Acquisition in Transformers

Study of capability acquisition in transformers tracking geometric changes and linear probes across model scales and algorithmic task difficulty levels.

Ax Aran Nayebi 4/3/2026

What Capable Agents Must Know: Selection Theorems for Robust Decision-Making under Uncertainty

Quantitative selection theorems proving that strong task performance under uncertainty necessitates world models and belief-like memory structures in agents.

Ax Haichen Hu, David Simchi-Levi 4/3/2026

Interleaved Resampling and Refitting: Data and Compute-Efficient Evaluation of Black-Box Predictors

Efficient evaluation algorithm for excess risk of large-scale empirical risk minimization using black-box access with single dataset.

Ax Sonia Laguna, Jorge da Silva Goncalves, Moritz Vandenhirtz, Alain Ryser, Irene Cannistraci, Julia E. Vogt 4/3/2026

Rethinking Machine Unlearning: Models Designed to Forget via Key Deletion

Machine unlearning approach using key deletion in model architecture for privacy-compliant data removal without requiring full training data access.

Ax Mohammad Al Ridhawi, Mahtab Haj Ali, Hussein Al Osman 4/3/2026

Adaptive Regime-Aware Stock Price Prediction Using Autoencoder-Gated Dual Node Transformers with Reinforcement Learning Control

Adaptive stock price prediction framework using autoencoder-gated dual node transformers with RL control for regime-dependent market behavior.

Ax Ming Shi, Yingbin Liang, Ness B. Shroff, Ananthram Swami 4/3/2026

Regret Bounds for Reinforcement Learning from Multi-Source Imperfect Preferences

Theoretical framework for RLHF with multi-source imperfect preferences, deriving regret bounds when feedback comes from multiple annotators with systematic mismatches.

Ax Yicheng Zou, Dongsheng Zhu, Lin Zhu, Tong Zhu, Yunhua Zhou, Peiheng Zhou, Xinyu Zhou, Dongzhan Zhou, Zhiwang Zhou, Yuhao Zhou, Bowen Zhou, Zhanping Zhong, Zhijie Zhong, Haiteng Zhao, Penghao Zhao, Xiaomeng Zhao, Zhiyuan Zhao, Yechen Zhang, Jin Zhang, Wenwei Zhang, Hongjie Zhang, Zhuo Zhang, Wenlong Zhang, Bo Zhang, Chao Zhang, Chen Zhang, Yuhang Zang, Fei Yuan, Jiakang Yuan, Jiashuo Yu, Jinhui Yin, Haochen Ye, Qian Yao, Bowen Yang, Danni Yang, Kaichen Yang, Ziang Yan, Jun Xu, Yicheng Xu, Wanghan Xu, Xuenan Xu, Chao Xu, Ruiliang Xu, Shuhao Xing, Long Xing, Xinchen Xie, Ling-I Wu, Zijian Wu, Zhenyu Wu, Lijun Wu, Yue Wu, Jianyu Wu, Wen Wu, Fan Wu, Xilin Wei, Qi Wei, Bingli Wang, Rui Wang, Ziyi Wang, Zun Wang, Yi Wang, Haomin Wang, Yizhou Wang, Lintao Wang, Yiheng Wang, Longjiang Wang, Bin Wang, Jian Tong, Zhongbo Tian, Huanze Tang, Chen Tang, Shixiang Tang, Yu Sun, Qiushi Sun, Xuerui Su, Qisheng Su, Chenlin Su, Demin Song, Jin Shi, Fukai Shang, Yuchen Ren, Pengli Ren, Xiaoye Qu, Yuan Qu, Jiantao Qiu, Yu Qiao, Biqing Qi, Runyu Peng, Tianshuo Peng, Jiahui Peng, Qizhi Pei, Zhuoshi Pan, Linke Ouyang, Wenchang Ning, Yichuan Ma, Zerun Ma, Ningsheng Ma, Runyuan Ma, Chengqi Lyu, Haijun Lv, Han Lv, Lindong Lu, Kuikun Liu, Jiangning Liu, Yuhong Liu, Kai Liu, Hongwei Liu, Zhoumianze Liu, Mengjie Liu, Ziyu Liu, Wenran Liu, Yang Liu, Liwei Liu, Kaiwen Liu, Junyao Lin, Junming Lin, Tianyang Lin, Dahua Lin, Jianze Liang, Linyang Li, Peiji Li, Zonglin Li, Zehao Li, Pengze Li, Guoyan Li, Lingkai Kong, Linglin Jing, Zhenjiang Jin, Feifei Jiang, Qian Jiang, Junhao Huang, Zixian Huang, Haian Huang, Zhouqi Hua, Ermo Hua, Han Hu, Linfeng Hou, Yinan He, Conghui He, Tianyao He, Xu Guo, Qipeng Guo, Aijia Guo, Yuzhe Gu, Lixin Gu, Jingyang Gong, Qiming Ge, Jiaye Ge, Songyang Gao, Jianfei Gao, Xinyu Fang, Caihua fan, Yue Fan, Yanhui Duan, Zichen Ding, Shengyuan Ding, Ning Ding, Xuanlang Dai, Erfei Cui, Ganqu Cui, Pei Chu, Tao Chu, Guangran Cheng, Yu Cheng, Kai Chen, Yongkang Chen, Chiyu Chen, Guanzhou Chen, Qiaosheng Chen, Sitao Chen, Xin Chen, Haojiong Chen, Yicheng Chen, Weihan Cao, Yuhang Cao, Qinglong Cao, Lei Bai 4/3/2026

Intern-S1-Pro: Scientific Multimodal Foundation Model at Trillion Scale

Trillion-parameter scientific multimodal foundation model with advanced agent capabilities spanning 100+ scientific domains and general reasoning tasks.

Ax Andrea Fraschini, Davide Tenedini, Riccardo Zamboni, Mirco Mutti, Marcello Restelli 4/3/2026

Unsupervised Behavioral Compression: Learning Low-Dimensional Policy Manifolds through State-Occupancy Matching

Method for learning low-dimensional policy manifolds in reinforcement learning through state-occupancy matching to improve sample efficiency.

Ax Tanvir Hossain, Muhammad Ifte Khairul Islam, Lilia Chebbah, Charles Fanning, Esra Akbas 4/3/2026

Cross-attentive Cohesive Subgraph Embedding to Mitigate Oversquashing in GNNs

Novel GNN architecture using cross-attentive cohesive subgraph embedding to address oversquashing and improve information flow in graph neural networks.

Ax Arsenios Scrivens 4/3/2026

Information-Theoretic Limits of Safety Verification for Self-Improving Systems

Theoretical analysis of safety verification limits for self-improving AI systems, formalizing compatibility between bounded risk and unbounded utility.

Ax Amirreza Alasti, Efe Erdal, Y\"ucel Celik, Theresa Eimer 4/3/2026

Learning to Play Blackjack: A Curriculum Learning Perspective

Uses LLM to dynamically generate curriculum over actions for RL agents, progressively introducing complex actions during training.

Ax Weyl Lu, Chenjie Hao, Yubei Chen 4/3/2026

Deep Networks Favor Simple Data

Studies how deep networks assign higher density to simpler out-of-distribution data than in-distribution test data.

Ax Junxian Wu, Chenghan Fu, Zhanheng Nie, Daoze Zhang, Bowen Wan, Wanxian Guan, Chuan Yu, Jian Xu, Bo Zheng 4/3/2026

MOON3.0: Reasoning-aware Multimodal Representation Learning for E-commerce Product Understanding

Multimodal representation learning framework for e-commerce product understanding combining reasoning with product attributes.

Ax Marwan Hassani, Tamara Verbeek, Sjoerd van Straten 4/3/2026

Chameleons do not Forget: Prompt-Based Online Continual Learning for Next Activity Prediction

Prompt-based continual learning method for next activity prediction that handles concept drift without catastrophic forgetting.

Ax Zhanzhi Lou, Hui Chen, Yibo Li, Qian Wang, Bryan Hooi 4/3/2026

Learning to Learn-at-Test-Time: Language Agents with Learnable Adaptation Policies

Language agents that learn adaptive policies at test-time through environment interactions, improving performance via iterative refinement.

Ax Zhantao Chen, Dongyi He, Jin Fang, Xi Chen, Yishuo Liu, Xiaozhen Zhong, Xuejun Hu 4/3/2026

Toward Personalized Darts Training: A Data-Driven Framework Based on Skeleton-Based Biomechanical Analysis and Motion Modeling

Data-driven framework using skeleton-based biomechanical analysis and motion modeling for personalized dart training.

Ax Xiangpeng Li, Yu-Hsuan Ho, Sam D Brody, Ali Mostafavi 4/3/2026

Property-Level Flood Risk Assessment Using AI-Enabled Street-View Lowest Floor Elevation Extraction and ML Imputation Across Texas

Pipeline using street-view image analysis and ML imputation to extract building elevation data for flood risk assessment in Texas.

Ax Amin Farajzadeh, Animesh Yadav, Halim Yanikomeroglu 4/3/2026

Tackling Non-IIDness in HAPS-Aided Federated Learning

Federated learning approach using HAPS networks with weighted client selection to handle non-IID data distributions.

Ax Kwangho Kim, Jisu Kim, Edward H. Kennedy 4/3/2026

Causal K-Means Clustering

Causal k-means clustering algorithm to identify heterogeneous treatment effects across unknown subgroups.

Ax Changdae Oh, Gyeongdeok Seo, Geunyoung Jung, Zhi-Qi Cheng, Hosik Choi, Jiyoung Jung, Kyungwoo Song 4/3/2026

Robust Adaptation of Foundation Models with Black-Box Visual Prompting

Parameter-efficient adaptation method for foundation models via black-box visual prompting without full parameter access.

Ax Ayoub Belhadji, Daniel Sharp, Youssef Marzouk 4/3/2026

Weighted quantization using MMD: From mean field to mean shift via gradient flows

Framework for approximating probability distributions using weighted particles via maximum mean discrepancy and gradient flows.

Ax Marta Adamska, Daria Smirnova, Hamid Nasiri, Zhengxin Yu, Peter Garraghan 4/3/2026

Green Prompting: Characterizing Prompt-driven Energy Costs of LLM Inference

Empirical study measuring how prompt and response characteristics impact energy consumption and inference costs of LLM operations.

Ax Ioannis Anagnostides, Gabriele Farina, Tuomas Sandholm, Brian Hu Zhang 4/3/2026

A Polynomial-Time Algorithm for Variational Inequalities under the Minty Condition

Develops polynomial-time algorithm for solving Stampacchia variational inequalities under the Minty condition.

Ax Junhui Zhang, Patrick Jaillet 4/3/2026

Multi-Timescale Primal Dual Hybrid Gradient with Application to Distributed Optimization

Proposes multi-timescale variants of primal-dual hybrid gradient algorithm for distributed optimization problems.

Ax Abdullah All Tanvir, Frank Y. Shih, Xin Zhong 4/3/2026

InvZW: Invariant Feature Learning via Noise-Adversarial Training for Robust Image Zero-Watermarking

Deep learning framework for image zero-watermarking using noise-adversarial training to learn distortion-invariant features.

Ax Kay Giesecke, Enguerrand Horel, Chartsiri Jirachotkulthorn 4/3/2026

AICO: Feature Significance Tests for Supervised Learning

Introduces AICO, a tool for testing feature significance in supervised learning models to improve interpretability and fairness.

Ax Alex Markham, Isaac Hirsch, Jeri A. Chang, Liam Solus, Bryon Aragam 4/3/2026

Intervening to Learn and Compose Causally Disentangled Representations

Presents method to train generative models that learn causally disentangled latent representations using context modules.

Ax David J Poland 4/3/2026

Boosted Enhanced Quantile Regression Neural Networks with Spatiotemporal Permutation Entropy for Complex System Prognostics

Proposes boosted quantile regression neural networks with entropy analysis for predicting patterns in complex dynamical systems.