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Engineering Preprint PDF DOI

AsyncShield: A Plug-and-Play Edge Adapter for Asynchronous Cloud-based VLA Navigation

Kai Yang, Zedong Chu, Yingnan Guo, Zhengbo Wang, Shichao Xie, Yanfen Shen, Xiaolong Wu, Xing Li, Mu Xu ยท 2026

While Vision-Language-Action (VLA) models have been demonstrated possessing strong zero-shot generalization for robot control, their massive parameter sizes typically necessitate cloud-based deploymenโ€ฆ

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AI & Data Science Preprint PDF DOI

FreeScale: Distributed Training for Sequence Recommendation Models with Minimal Scaling Cost

Chenhao Feng, Haoli Zhang, Shakhzod Ali-Zade, Yanli Zhao, Liang Luo, Jennifer Cao, Lisen Deng, Siqiao Chen, Chenyu Zhao, Tristan Rice, Daniel Johnson, Min Si, Tiantu Xu, Yi Zhang, Siqi Yan, Chuanhao Zhuge, Min Ni, Bi Xue, Qunshu Zhang, Shen Li ยท 2026

Modern industrial Deep Learning Recommendation Models typically extract user preferences through the analysis of sequential interaction histories, subsequently generating predictions based on these deโ€ฆ

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AI & Data Science Preprint PDF DOI

Grounding Before Generalizing: How AI Differs from Humans in Causal Transfer

Liangru Xiang, Yuxi Ma, Zhihao Cao, Yixin Zhu, Song-Chun Zhu ยท 2026

Extracting abstract causal structures and applying them to novel situations is a hallmark of human intelligence. While Large Language Models (LLMs) and Vision Language Models (VLMs) have shown strong โ€ฆ

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Economics & Finance Preprint PDF DOI

Difference-in-differences with a mediator

Yuhao Deng, Haoyu Wei, Zhongzhe Ouyang ยท 2026

Causal mediation analysis is a powerful tool for disentangling the total effect of a treatment into its direct effect on the outcome and its indirect effect mediated through an intermediate variable. โ€ฆ

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Computer Science Preprint PDF DOI

Disagreement as Signals: Dual-view Calibration for Sequential Recommendation Denoising

Sijia Li, Min Gao, Zongwei Wang, Zhiyi Liu, Xin Xia, Yi Zhang ยท 2026

Sequential recommendation seeks to model the evolution of user interests by capturing temporal user intent and item-level transition patterns. Transformer-based recommenders demonstrate a strong capacโ€ฆ

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AI & Data Science Preprint PDF DOI

Generalising maximum mean discrepancy: kernelised functional Bregman divergences

Russell Tsuchida, Frank Nielsen ยท 2026

Bregman divergences play a pivotal role in statistics, machine learning and computational information geometry. Particularly in the context of machine learning, they are central to clustering, exponenโ€ฆ

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AI & Data Science Preprint PDF DOI

CLLAP: Contrastive Learning-based LiDAR-Augmented Pretraining for Enhanced Radar-Camera Fusion

Bingyi Liu, Chuanhui Zhu, Hongfei Xue, Jian Teng, Jipeng Liu, Enshu Wang, Penglin Dai, Pu Wang ยท 2026

Accurate 3D object detection is critical for autonomous driving, necessitating reliable, cost-effective sensors capable of operating in adverse weather conditions. Camera and millimeter-wave radar fusโ€ฆ

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AI & Data Science Preprint PDF DOI

End-to-End Learning for Partially-Observed Time Series with PyPOTS

Wenjie Du, Yiyuan Yang, Tianxiang Zhan, Qingsong Wen ยท 2026

Partially-observed time series (POTS) is ubiquitous in real-world applications, yet most existing toolchains separate missing-value handling from downstream learning, which limits reproducibility and โ€ฆ

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AI & Data Science Preprint PDF DOI

A Limit Theory of Foundation Models: A Mathematical Approach to Understanding Emergent Intelligence and Scaling Laws

Jun Shu, Junxiong Jia, Deyu Meng, Zongben Xu ยท 2026

Emergent intelligence have played a major role in the modern AI development. While existing studies primarily rely on empirical observations to characterize this phenomenon, a rigorous theoretical fraโ€ฆ

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Physics Preprint PDF DOI

LStein: A new approach to visualizing sparse 2.5-dimensional data

Lukas Steinwender, Anais Moller, Christopher J. Fluke ยท 2026

Visualization of high-dimensional data is crucial to retrieve all the knowledge that is contained within a dataset. Effective and informative presentation of three-dimensional data via a two-dimensionโ€ฆ

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AI & Data Science Preprint PDF DOI

DeepTaxon: An Interpretable Retrieval-Augmented Multimodal Framework for Unified Species Identification and Discovery

Jiawei Wang, Ming Lei, Yaning Yang, Xinyan Lin, Yuquan Le, Qiwei Ma, Zhiwei Xu, Zheqi Lv, Yuchen Ang, Zhe Quan, Tat-Seng Chua ยท 2026

Identifying species in biology among tens of thousands of visually similar taxa while discovering unknown species in open-world environments remains a fundamental challenge in biodiversity research. Cโ€ฆ

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Engineering Preprint PDF DOI

IPRU: Input-Perturbation-based Radio Frequency Fingerprinting Unlearning for LAWNs

Ce Liu, Rui Meng, Yinqiu Liu, Xiaodong Xu, Yi Ma, Rahim Tafazolli, Ping Zhang ยท 2026

Radio Frequency Fingerprinting (RFF) is a key technology for identity authentication in wireless networks. However, due to the rapid dynamics of Autonomous Aerial Vehicles (AAVs) in low-altitude wirelโ€ฆ

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AI & Data Science Preprint PDF DOI

Geometry-Aware Offline-to-Online Learning in Linear Contextual Bandits

Zean Han, Ruihan Lin, Zezhen Ding, Jiheng Zhang ยท 2026

We study offline-to-online learning in linear contextual bandits with biased offline regression data: the offline parameter need not match the online one, so history should not be treated as a single โ€ฆ

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Computer Science Preprint PDF DOI

QubitQuest: Learning Quantum Computing through Mini-Games

Bella Hill, Miguel Morales-Trujillo ยท 2026

Quantum Computing (QC) is often challenging for beginners due to its abstract concepts and mathematical foundations. This paper explores the use of gamification to support the learning of introductoryโ€ฆ

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AI & Data Science Preprint PDF DOI

FedSLoP: Memory-Efficient Federated Learning with Low-Rank Gradient Projection

Yutong He, Zhengyang Huang, Jiahe Geng ยท 2026

Federated learning enables a population of clients to collaboratively train machine learning models without exchanging their raw data, but standard algorithms such as FedAvg suffer from slow convergenโ€ฆ

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Mathematics Preprint PDF DOI

Adaptive-Distribution Randomized Neural Networks for PDEs: A Low-Dimensional Distribution-Learning Framework

You Yang, Fei Wang ยท 2026

Randomized neural networks (RaNNs) are attractive for partial differential equations (PDEs) because they replace expensive end-to-end training with a linear least-squares solve over randomized hidden โ€ฆ

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AI & Data Science Preprint PDF DOI

EPM-RL: Reinforcement Learning for On-Premise Product Mapping in E-Commerce

Minhyeong Yu, Wonduk Seo ยท 2026

Product mapping, the task of deciding whether two e-commerce listings refer to the same product, is a core problem for price monitoring and channel visibility. In real marketplaces, however, sellers fโ€ฆ

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AI & Data Science Preprint PDF DOI

Hindsight Preference Optimization for Financial Time Series Advisory

Yanwei Cui, Guanghui Wang, Xing Zhang, Peiyang He, Ziyuan Li, Bing Zhu, Wei Qiu, Xusheng Wang, Zheng Yu, Anqi Xin ยท 2026

Time series models predict numbers; decision-makers need advisory -- directional signals with reasoning, actionable suggestions, and risk management. Training language models for such predictive advisโ€ฆ

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AI & Data Science Preprint PDF DOI

Continual Calibration: Coverage Can Collapse Before Accuracy in Lifelong LLM Fine-Tuning

Ibne Farabi Shihab, Sanjeda Akter, Anuj Sharma ยท 2026

Continual learning for large language models is typically evaluated through accuracy retention under sequential fine-tuning. We argue that this perspective is incomplete, because uncertainty reliabiliโ€ฆ

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AI & Data Science Preprint PDF DOI

Hierarchical Prototype-based Domain Priors for Multiple Instance Learning in Multimodal Histopathology Analysis

Xuemei Qiu, Dawei Fan, Yebin Huang, Yanping Chen, Lifang Wei ยท 2026

Digital pathology has fundamentally altered diagnostic workflows by enabling the computational analysis of gigapixel Whole Slide Images (WSIs), yet effectively deciphering their complex tumor microenvโ€ฆ

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