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AI & Data Science Preprint PDF DOI

RemoteShield: Enable Robust Multimodal Large Language Models for Earth Observation

Rui Min, Liang Yao, Shiyu Miao, Shengxiang Xu, Yuxuan Liu, Chuanyi Zhang, Shimin Di, Fan Liu ยท 2026

A robust Multimodal Large Language Model (MLLM) for Earth Observation should maintain consistent interpretation and reasoning under realistic input variations. However, current Remote Sensing MLLMs faโ€ฆ

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Engineering Preprint PDF DOI

GaLa: Hypergraph-Guided Visual Language Models for Procedural Planning

Kun Wang, Yiming Li, Mingcheng Qu, Aqiang Zhang, Guang Yang, Tonghua Su ยท 2026

Implicit spatial relations and deep semantic structures encoded in object attributes are crucial for procedural planning in embodied AI systems. However, existing approaches often over rely on the reaโ€ฆ

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Mathematics Preprint PDF DOI

Bootstrap consistency for general double/debiased machine learning estimators

Ziming Lin, Fang Han ยท 2026

Double/debiased machine learning (DML) provides a general framework for inference with high-dimensional or otherwise complex nuisance parameters by combining Neyman-orthogonal scores with cross-fittinโ€ฆ

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Mathematics Preprint PDF DOI

Learning Mixtures of Nonparametric and Convolutional Measures on Effectively Low-dimensional Affine Spaces

Sunrit Chakraborty, XuanLong Nguyen ยท 2026

In this paper, we develop a finite mixture of convolutional distributions, a statistical model to analyze continuous data distributed approximately on a mixture of low-dimensional affine subspaces. Thโ€ฆ

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Earth & Environmental Sciences Preprint PDF DOI

Massive-scale unlabeled field and labeled synthetic seismic datasets of global shelf-edge clinothems

Hui Gao, Xinming Wu, Jintao Li, Xiaoming Sun, Jiarun Yang ยท 2026

Seismic stratigraphic interpretation of shelf-edge clinothems is essential for revealing tectonic evolution, paleoclimate change, depositional dynamic conditions, and hydrocarbon generation and accumuโ€ฆ

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AI & Data Science Preprint PDF DOI

Fringe Projection Based Vision Pipeline for Autonomous Hard Drive Disassembly

Badrinath Balasubramaniam, Vignesh Suresh, Benjamin Metcalf, Beiwen Li ยท 2026

Unrecovered e-waste represents a significant economic loss. Hard disk drives (HDDs) comprise a valuable e-waste stream necessitating robotic disassembly. Automating the disassembly of HDDs requires hoโ€ฆ

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Computer Science Preprint PDF DOI

Cloud-native and Distributed Systems for Efficient and Scalable Large Language Models -- A Research Agenda

Minxian Xu, Jingfeng Wu, Shengye Song, Satish Narayana Srirama, Bahman Javad, Rajiv Ranjan, Devki Nandan Jha, Sa Wang, Wenhong Tian, Huanle Xu, Li Li, Zizhao Mo, Shuo Ren, Thomas Kunz, Petar Kochovski, Vlado Stankovski, Kejiang Ye, Chengzhong Xu, Rajkumar Buyya ยท 2026

The rapid rise of Large Language Models (LLMs) has revolutionized various artificial intelligence (AI) applications, from natural language processing to code generation. However, the computational demโ€ฆ

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AI & Data Science Preprint PDF DOI

Region-Affinity Attention for Whole-Slide Breast Cancer Classification in Deep Ultraviolet Imaging

Nagur Shareef Shaik, Teja Krishna Cherukuri, Dong Hye Ye ยท 2026

Breast cancer diagnosis demands rapid and precise tools, yet traditional histopathological methods often fall short in intra-operative settings. Deep Ultraviolet (DUV) fluorescence imaging emerges as โ€ฆ

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AI & Data Science Preprint PDF DOI

PAC-Bayes Bounds for Gibbs Posteriors via Singular Learning Theory

Chenyang Wang, Yun Yang ยท 2026

We derive explicit non-asymptotic PAC-Bayes generalization bounds for Gibbs posteriors, that is, data-dependent distributions over model parameters obtained by exponentially tilting a prior with the eโ€ฆ

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AI & Data Science Preprint PDF DOI

Cross-Modal Attention Analysis and Optimization in Vision-Language Models: A Study on Visual Reliability

Lijie Zhou ยท 2026

Vision-Language Models (VLMs) achieve strong cross-modal performance, yet recent evidence suggests they over-rely on textual descriptions while under-utilizing visual evidence -- a phenomenon termed `โ€ฆ

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AI & Data Science Preprint PDF DOI

Continual Safety Alignment via Gradient-Based Sample Selection

Thong Bach, Dung Nguyen, Thao Minh Le, Truyen Tran ยท 2026

Large language models require continuous adaptation to new tasks while preserving safety alignment. However, fine-tuning on even benign data often compromises safety behaviors, including refusal of haโ€ฆ

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AI & Data Science Preprint PDF DOI

Beyond the Basics: Leveraging Large Language Model for Fine-Grained Medical Entity Recognition

Nwe Ni Win, Jim Basilakis, Steven Thomas, Seyhan Yazar, Laura Pierce, Stephanie Liu, Paul M. Middleton, Nasser Ghadiri, X. Rosalind Wang ยท 2026

Extracting clinically relevant information from unstructured medical narratives such as admission notes, discharge summaries, and emergency case histories remains a challenge in clinical natural languโ€ฆ

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Mathematics Preprint PDF DOI

Symplectic Inductive Bias for Data-Driven Target Reachability in Hamiltonian Systems

Zhuo Ouyang, Jixian Liu, Enrique Mallada ยท 2026

Inductive bias refers to restrictions on the hypothesis class that enable a learning method to generalize effectively from limited data. A canonical example in control is linearity, which underpins loโ€ฆ

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AI & Data Science Preprint PDF DOI

Guardrails in Logit Space: Safety Token Regularization for LLM Alignment

Thong Bach, Truyen Tran ยท 2026

Fine-tuning well-aligned large language models (LLMs) on new domains often degrades their safety alignment, even when using benign datasets. Existing safety alignment techniques primarily focus on preโ€ฆ

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AI & Data Science Preprint PDF DOI

CDSA-Net:Collaborative Decoupling of Vascular Structure and Background for High-Fidelity Coronary Digital Subtraction Angiography

Si Li, Chen-Kai Hu, Zhenhuan Lyu, Yuanqing He ยท 2026

Digital subtraction angiography (DSA) in coronary imaging is fundamentally challenged by physiological motion, forcing reliance on raw angiograms cluttered with anatomical noise. Existing deep learninโ€ฆ

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AI & Data Science Preprint PDF DOI

Demystifying the unreasonable effectiveness of online alignment methods

Enoch Hyunwook Kang ยท 2026

Iterative alignment methods based on purely greedy updates are remarkably effective in practice, yet existing theoretical guarantees of \(O(\log T)\) KL-regularized regret can seem pessimistic relativโ€ฆ

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Physics Preprint PDF DOI

Double Descent in Quantum Kernel Ridge Regression

Kensuke Kamisoyama, Lento Nagano, Koji Terashi ยท 2026

Various classical machine learning models, including linear regression, kernel methods, and deep neural networks, exhibit double descent, in which the test risk peaks near the interpolation threshold โ€ฆ

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Engineering Preprint PDF DOI

Robust Resource Allocation in RIS-Assisted Wireless Networks Integrating NOMA and Over-the-Air Federated Learning

Saeid Pakravan, Mohsen Ahmadzadeh, Ming Zeng, Ghosheh Abed Hodtani, Xingwang Li, Ji Wang, Gongpu Wang ยท 2026

This paper addresses the critical issue of spectrum scarcity and the need to support diverse services, including communication and learning tasks, by presenting a reconfigurable intelligent surface (Rโ€ฆ

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AI & Data Science Preprint PDF DOI

Learning to Control Summaries with Score Ranking

Hongye Liu, Liang Ding, Ricardo Henao ยท 2026

Recent advances in summarization research focus on improving summary quality across multiple criteria, such as completeness, conciseness, and faithfulness, by jointly optimizing these dimensions. Howeโ€ฆ

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Engineering Preprint PDF DOI

CADRE: Card-Agnostic Domain-Aligned RF Embeddings for Virtual PIN Pads on Passive NFC Cards

Dickson Akuoko Sarpong, Hongzhi Guo ยท 2026

Near Field Communication (NFC) cards are widely used for identification, but their passive nature often limits the ability to incorporate additional security mechanisms. As a result, anyone holding thโ€ฆ

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