Ax Ya Zhou, Tianxiang Hao, Ziyi Cai, Haojie Zhu, Kejun He, Jia Liu, Xiaohan Fan, Jing Yuan 4/7/2026

Detecting low left ventricular ejection fraction from ECG using an interpretable and scalable predictor-driven framework

Develops interpretable ML framework for detecting low left ventricular ejection fraction from ECG data.

Ax Ikechukwu Uchendu, Swati Goel, Karly Hou, Ebrahim Songhori, Kuang-Huei Lee, Joe Wenjie Jiang, Vijay Janapa Reddi, Vincent Zhuang 4/7/2026

See it to Place it: Evolving Macro Placements with Vision-Language Models

Applies Vision-Language Models to chip floorplanning macro placement optimization tasks.

Ax Liliang Ren, Yang Liu, Yelong Shen, Weizhu Chen 4/7/2026

Rethinking Language Model Scaling under Transferable Hypersphere Optimization

Introduces HyperP, hypersphere parameterization for LLM scaling with improved stability and hyperparameter transfer.

Ax Ivan Pasichnyk 4/7/2026

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

Proposes time-varying momentum schedule derived from critically damped harmonic oscillator for neural network training optimization.

Ax Chihan Huang, Huaijin Wang, Shuai Wang 4/7/2026

ReproMIA: A Comprehensive Analysis of Model Reprogramming for Proactive Membership Inference Attacks

Research on membership inference attacks against deep learning models using model reprogramming to reduce computational costs of privacy auditing.

Ax Zichao Wei 4/7/2026

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

arXiv paper analyzing integer multiplication as hard problem for neural networks. Theoretical analysis challenging assumptions about long-range dependencies in neural computation.

Ax Lucas Riera Abbade, Anna Helena Reali Costa 4/7/2026

Realistic Market Impact Modeling for Reinforcement Learning Trading Environments

arXiv paper on realistic market impact modeling for RL trading agents. Gymnasium-compatible environments with nonlinear transaction costs for algorithmic trading research.

Ax Gabriel U. Talasso, Meghdad Kurmanji, Allan M. de Souza, Nicholas D. Lane, Leandro A. Villas 4/7/2026

Task-Centric Personalized Federated Fine-Tuning of Language Models

arXiv paper on personalized federated fine-tuning of language models. Federated learning approach for task-centric LLM adaptation on private distributed data.

Ax Amirhossein Dezhboro, Fateme Maleki, Arman Adibi, Erfan Amini, Jose E. Ramirez-Marquez 4/7/2026

Convergence of Byzantine-Resilient Gradient Tracking via Probabilistic Edge Dropout

arXiv paper on Byzantine-resilient distributed optimization with probabilistic edge dropout. Convergence analysis for distributed learning with adversarial agents.

Ax Bj\"orn Roman Kohlberger (EctoSpace, Dublin, Ireland) 4/7/2026

Spectral Compact Training: Pre-Training Large Language Models via Permanent Truncated SVD and Stiefel QR Retraction

arXiv paper on memory-efficient LLM pre-training via truncated SVD factorization. Method reduces memory footprint for training large language models on consumer hardware.

Ax Nikita Gabdullin, Ilya Androsov 4/7/2026

Using predefined vector systems to speed up neural network multimillion class classification

arXiv paper on O(1) complexity label prediction for neural networks with millions of classes. Optimization technique for efficient classification in high-dimensional spaces.

Ax Zheng Zhang, Cuong C. Nguyen, David Rosewarne, Kevin Wells, Gustavo Carneiro 4/7/2026

Fatigue-Aware Learning to Defer via Constrained Optimisation

arXiv paper on human-AI cooperation via fatigue-aware deferral systems. ML method modeling human fatigue to optimize when AI should defer to humans.

Ax Ken M. Nakanishi 4/7/2026

Screening Is Enough

arXiv paper introducing Multiscreen attention mechanism for language models. Alternative to softmax attention enabling absolute relevance scoring in transformers.

Ax Rafael Pardinas, Ehsan Kamalloo, David Vazquez, Alexandre Drouin 4/7/2026

Apriel-1.5-OpenReasoner: RL Post-Training for General-Purpose and Efficient Reasoning

arXiv paper on reinforcement learning post-training for reasoning models. Open-weight model training using verifiable rewards across diverse reasoning domains.

Ax Zun Li, Marc Lanctot, Kevin R. McKee, Luke Marris, Ian Gemp, Daniel Hennes, Paul Muller, Kate Larson, Yoram Bachrach, Michael P. Wellman 4/7/2026

Combining Tree-Search, Generative Models, and Nash Bargaining Concepts in Game-Theoretic Reinforcement Learning

arXiv paper on opponent modeling in game-theoretic reinforcement learning using tree-search and generative models. Research on scalable multi-agent RL methods.

Ax Rishabh Dixit, Mert Gurbuzbalaban, Waheed U. Bajwa 4/7/2026

Accelerated Gradient Methods for Nonconvex Optimization: Escape Trajectories From Strict Saddle Points and Convergence to Local Minima

Theoretical analysis of accelerated gradient methods for nonconvex optimization and convergence to local minima.

Ax Dinesh Sharma, Ankit Shah, Chaitra Gopalappa 4/7/2026

A Multi-Agent Reinforcement Learning Framework for Public Health Decision Analysis

Multi-agent reinforcement learning framework for HIV prevention policy optimization across U.S. regions.

Ax Ant\'onio Filgueiras, Eduardo R. B. Marques, Lu\'is M. B. Lopes, Miguel Marques, Hugo Silva 4/7/2026

Floralens: a Deep Learning Model for the Portuguese Native Flora

Deep CNN model trained on Portuguese native flora dataset for species identification in citizen science.

Ax Changdae Oh, Gyeongdeok Seo, Geunyoung Jung, Zhi-Qi Cheng, Hosik Choi, Jiyoung Jung, Kyungwoo Song 4/7/2026

Robust Adaptation of Foundation Models with Black-Box Visual Prompting

Black-box visual prompting method for parameter-efficient transfer learning of foundation models without full parameter access.

Ax Lechen Zhang, Tolga Ergen, Lajanugen Logeswaran, Moontae Lee, David Jurgens 4/7/2026

SPRIG: Improving Large Language Model Performance by System Prompt Optimization

SPRIG: Genetic algorithm for optimizing system prompts in LLMs to improve task performance.

Ax Muralikrishnna G. Sethuraman, Razieh Nabi, Faramarz Fekri 4/7/2026

MissNODAG: Differentiable Cyclic Causal Graph Learning from Incomplete Data

MissNODAG: Framework for learning cyclic causal graphs from incomplete data using differentiable methods.

Ax Haitham Kanj, Seonho Kim, Kiryung Lee 4/7/2026

Sparse Max-Affine Regression

Sparse Gradient Descent algorithm for variable selection in convex piecewise linear regression models.

Ax Hao Chen, Kai Yi, Yu Guang Wang 4/7/2026

Score-matching-based Structure Learning for Temporal Data on Networks

Score-matching causal discovery algorithm extended for temporal data on networks.

Ax Ugur Dar, Mustafa Cavus 4/7/2026

From XAI to MLOps: Explainable Concept Drift Detection with Profile Drift Detection

XAI-based method combining explainability with concept drift detection for monitoring model performance degradation.

Ax Aytijhya Saha, Aaditya Ramdas 4/7/2026

Post-detection inference for sequential changepoint localization

Framework for constructing confidence sets for changepoints in sequential analysis using data-dependent stopping times.

Ax Qi Wang, Zhipeng Zhang, Baao Xie, Xin Jin, Yunbo Wang, Shiyu Wang, Liaomo Zheng, Xiaokang Yang, Wenjun Zeng 4/7/2026

Disentangled World Models: Learning to Transfer Semantic Knowledge from Distracting Videos for Reinforcement Learning

World models using disentangled representations to transfer semantic knowledge from distracting videos for RL agents.

Ax Henri A\"idasso, Francis Bordeleau, Ali Tizghadam 4/7/2026

Towards Build Optimization Using Digital Twins

Digital twins framework for optimizing CI/CD build processes to reduce duration, failures, and flakiness.

Ax Kejie Zhao, Wenjia Hua, Aiersi Tuerhong, Luziwei Leng, Yuxin Ma, Qinghai Guo 4/7/2026

Threshold Modulation for Online Test-Time Adaptation of Spiking Neural Networks

Online test-time adaptation for spiking neural networks on neuromorphic chips to handle distribution shifts.

Ax Yifu Yuan, Haiqin Cui, Yibin Chen, Zibin Dong, Fei Ni, Longxin Kou, Jinyi Liu, Pengyi Li, Yan Zheng, Jianye Hao 4/7/2026

From Seeing to Doing: Bridging Reasoning and Decision for Robotic Manipulation

FSD framework combining vision-language models with robotic action models for zero-shot manipulation in novel scenarios.

Ax Gordana Ispirova, Michael Sebek, Giulia Menichetti 4/7/2026

Informatics for Food Processing

Review of ML/AI applications in food processing, classification systems, and food informatics.

Ax Yash Patel, Unique Subedi, Ambuj Tewari 4/7/2026

Operator Learning for Schr\"{o}dinger Equation: Unitarity, Error Bounds, and Time Generalization

Neural network surrogate for learning evolution operators in time-dependent Schrödinger equations with unitarity constraints.

Ax Edward L. Wang, Mohammad Sharifi Kiasari, Tianyu Wang, Hayden Helm, Avanti Athreya, Carey Priebe, Vince Lyzinski 4/7/2026

Gaussian mixture models as a proxy for interacting language models

Gaussian mixture models as computationally efficient proxy for LLM+RAG systems combining multiple models.

Ax Tianze Yang, Tyson Jordan, Ruitong Sun, Ninghao Liu, Jin Sun 4/7/2026

Common Inpainted Objects In-N-Out of Context

COinCO dataset with 97,722 images created via diffusion-based inpainting for training context-aware vision models.

Ax Peter Sentz, Stanley Nicholson, Yujin Cho, Sohail Reddy, Brendan Keith, Stefanie G\"unther 4/7/2026

Learning thermodynamic master equations for open quantum systems

Machine learning methods for learning Hamiltonian components of open quantum systems.

Ax Yingli Wang, Changwei Tu, Xiaoyu Wang, Lingjiong Zhu 4/7/2026

Accelerating Constrained Sampling: A Large Deviations Approach

Large deviations approach to accelerate constrained sampling algorithms for probability distributions.

Ax Nikolay Blagoev, O\u{g}uzhan Ersoy, Lydia Yiyu Chen 4/7/2026

All is Not Lost: LLM Recovery without Checkpoints

Technique to recover LLM training on decentralized/spot nodes from partial model loss without full checkpoints.

Ax Yukun Huang, Sanxing Chen, Jian Pei, Manzil Zaheer, Bhuwan Dhingra 4/7/2026

Cite Pretrain: Retrieval-Free Knowledge Attribution for Large Language Models

Method for LLMs to reliably cite source documents seen during training without external retrievers at inference time.

Ax Lujun Li, Yiqun Wang, Radu State 4/7/2026

Vision Transformer-Based Time-Series Image Reconstruction for Cloud-Filling Applications

Vision Transformer framework reconstructs cloud-obscured satellite imagery using time-series data for crop mapping.

Ax Takuro Kawada, Shunsuke Kitada, Sota Nemoto, Hitoshi Iyatomi 4/7/2026

SciGA: A Comprehensive Dataset for Designing Graphical Abstracts in Academic Papers

SciGA-145k dataset for training models to automatically design graphical abstracts for academic papers using visual data.

Ax Dixon Domfeh, Saeid Safarveisi 4/7/2026

CATNet: A geometric deep learning approach for CAT bond spread prediction in the primary market

CATNet applies graph convolutional networks to predict catastrophe bond spreads using relational data structures.

Ax Tomer Krichli, Bhiksha Raj, Joseph Keshet 4/7/2026

WhisperRT -- Turning Whisper into a Causal Streaming Model

Modification of Whisper ASR model to enable low-latency streaming transcription through architectural and training changes.

Ax Yifu Yuan, Haiqin Cui, Yaoting Huang, Yibin Chen, Fei Ni, Zibin Dong, Pengyi Li, Yan Zheng, Hongyao Tang, Jianye Hao 4/7/2026

Embodied-R1: Reinforced Embodied Reasoning for General Robotic Manipulation

Vision-language model for robotic manipulation using embodiment-agnostic pointing representation to address generalization in embodied AI.

Ax Wangsong Yin, Daliang Xu, Mengwei Xu, Gang Huang, Xuanzhe Liu 4/7/2026

ShadowNPU: System and Algorithm Co-design for NPU-Centric On-Device LLM Inference

System co-design for efficient on-device LLM inference on NPU hardware, optimizing attention operations for privacy-preserving deployment.

Ax Xinwen Liu, Lei Qian, Song Xi Chen, Niansheng Tang 4/7/2026

Partially Functional Dynamic Backdoor Diffusion-based Causal Model

Diffusion-based causal inference method for spatio-temporal data with unmeasured confounders and multi-resolution observations.

Ax Ivan Lau, Jonathan Scarlett 4/7/2026

Sequential 1-bit Mean Estimation with Near-Optimal Sample Complexity

Theoretical work on distributed mean estimation with 1-bit communication constraints using interval queries, achieving near-optimal sample complexity.

Ax Vincent Nguyen, Guilherme Herzog, Jos\'e Cambronero, Marcus Revaj, Aditya Kini, Alexander Fr\"ommgen, Maxim Tabachnyk 4/7/2026

Smart Paste: Automatically Fixing Copy/Paste for Google Developers

Google developer tool using deep learning to automatically fix copy/paste code, predicting required edits from formatting to cross-language translation.

Ax Sicheng Lyu, Yu Gu, Xinyu Wang, Jerry Huang, Sitao Luan, Yufei Cui, Xiao-Wen Chang, Peng Lu 4/7/2026

EvoEdit: Evolving Null-space Alignment for Robust and Efficient Knowledge Editing

Knowledge editing method for LLMs enabling sequential updates through null-space alignment, improving robustness in continual model editing scenarios.

Ax Chun Chet Ng, Zhen Hao Chu, Jia Yu Lim, Yin Yin Boon, Wei Zeng Low, Jin Khye Tan 4/7/2026

AI-BAAM: AI-Driven Bank Statement Analytics as Alternative Data for Malaysian MSME Credit Scoring

AI system for credit scoring of Malaysian MSMEs using bank statement data as alternative to traditional credit bureau data.

Ax Pankaj K Mishra, Sanni Laaksonen, Jochen Kamm, Anand Singh 4/7/2026

Three-dimensional inversion of gravity data using implicit neural representations and scientific machine learning

Scientific machine learning approach using implicit neural representations for 3D gravity inversion, modeling subsurface density as continuous field.

Ax Hashem Omrani, Raha Imanirad, Adam Diamant, Utkarsh Verma, Amol Verma, Fahad Razak 4/7/2026

Endogenous Aggregation of Multiple Data Envelopment Analysis Scores for Large Data Sets

Data envelopment analysis method for dynamic efficiency evaluation across multiple organizational dimensions with regularization for large-scale settings.