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Showing 957942 results for "user computer interface"
AI & Data Science Preprint PDF DOI

Robust Learning on Heterogeneous Graphs with Heterophily: A Graph Structure Learning Approach

Yihan Zhang, Ercan E. Kuruoglu ยท 2026

Heterogeneous graphs with heterophily have emerged as a powerful abstraction for modeling complex real-world systems, where nodes of different types and labels interact in diverse and often non-homophโ€ฆ

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Engineering Preprint PDF DOI

An Experimental Modular Instrument With a Haptic Feedback Framework for Robotic Surgery Training

Walid Shaker, Mustafa Suphi Erden ยท 2026

Robotic-assisted surgery offers significant clinical advantages but largely eliminates direct haptic feedback, increasing the risk of excessive tool-tissue interaction forces. Although recent commerciโ€ฆ

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Computer Science Preprint PDF DOI

RCW-CIM: A Digital CIM-based LLM Accelerator with Read-Compute/Write

Yan-Cheng Guo, Tian-Sheuan Chang, Jian-Wei Su ยท 2026

Digital computing-in-memory (DCIM) has emerged as a promising solution for large language model (LLM) acceleration by minimizing data transfers between external DRAM and on-chip accelerators while maiโ€ฆ

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Mathematics Preprint PDF DOI

Mean-Field Systems with Heterogeneous Subteams: Optimality of Cluster-Symmetric Independent Policies and Equivalence with Decentralized McKean-Vlasov Control of Cluster-Representative Agents

Connor S. Braun, Sina Sanjari, Naci Saldi, Gunnar Blohm, Serdar Yuksel ยท 2026

Across science and engineering, mean-field methods have been a powerful and versatile approach for the analysis of systems of many interacting elements. However, common arguments used to characterize โ€ฆ

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AI & Data Science Preprint PDF DOI

Proactive Dialogue Model with Intent Prediction

Yang Luo ยท 2026

Dialogue models are inherently reactive, responding to the current user turn without anticipating upcoming intents, which leads to redundant interactions in multi-intent settings. We address this limiโ€ฆ

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AI & Data Science Preprint PDF DOI

Emotion-Aware Clickbait Attack in Social Media

Syed Mhamudul Hasan, Mohd. Farhan Israk Soumik, Abdur R. Shahid ยท 2026

Clickbait is characterized by disproportionately high emotional intensity relative to informational content, often reinforced by specific structural patterns. However, current research considers clickโ€ฆ

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AI & Data Science Preprint PDF DOI

Stable but Wrong: An Inference Limit in Galactic Archaeology

Zhipeng Zhang ยท 2026

Statistical inference in observational science typically relies on a fundamental assumption: as sample size increases and uncertainties decrease, the inferred results should converge to the true physiโ€ฆ

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Computer Science Preprint PDF DOI

From Notepad AI to Social Media: How Can Text Style Transformation Mitigate Social Harm?

Syed Mhamudul Hasan, Mohd. Farhan Israk Soumik, Abdur R. Shahid ยท 2026

The rapid proliferation of harmful and emotionally damaging content on social media platforms has intensified concerns regarding societal harm. While content moderation efforts primarily focus on deteโ€ฆ

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AI & Data Science Preprint PDF DOI

Hyperspectral Image Classification via Efficient Global Spectral Supertoken Clustering

Peifu Liu, Tingfa Xu, Jie Wang, Huan Chen, Huiyan Bai, Jianan Li ยท 2026

Hyperspectral image classification demands spatially coherent predictions and precise boundary delineation. Yet prevailing superpixel-based methods face an inherent contradiction: clustering aggregateโ€ฆ

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Computer Science Preprint PDF DOI

A note on the parameter $\ell$ in Buchbinder--Feldman's deterministic submodular matroid algorithm

Shisheng Li ยท 2026

Buchbinder and Feldman recently gave a deterministic $(1-1/e-\varepsilon)$-approximation for maximizing a non-negative monotone submodular function subject to a matroid constraint, with query complexiโ€ฆ

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AI & Data Science Preprint PDF DOI

TypeBandit: Type-Level Context Allocation and Reweighting for Effective Attribute Completion in Heterogeneous Graph Neural Networks

Ta-Yang Wang, Rajgopal Kannan, Viktor Prasanna ยท 2026

Heterogeneous graphs are widely used to model multi-relational systems, but missing node attributes remain a major bottleneck for downstream learning. In this paper, we identify and formalize type-depโ€ฆ

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Mathematics Preprint PDF DOI

Over-Approximating Minimizer Sets of Constrained Convex Programs with Parametric Uncertainty via Reachability Analysis

Brendan Gould, Chih-Yuan Chiu, Antoine P. Leeman, Kyriakos G. Vamvoudakis, Samuel Coogan, Glen Chou ยท 2026

We study the set of solutions to a parameterized, strongly convex optimization problem whose cost depends on uncertain, bounded parameters. We compute a certified outer approximation of the correspondโ€ฆ

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AI & Data Science Preprint PDF DOI

CoAX: Cognitive-Oriented Attribution eXplanation User Model of Human Understanding of AI Explanations

Louth Bin Rawshan, Zhuoyu Wang, Brian Y. Lim ยท 2026

Explainable AI (XAI) aims to improve user understanding and decisions when using AI models. However, despite innovations in XAI, recent user evaluations reveal that this goal remains elusive. Understaโ€ฆ

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AI & Data Science Preprint PDF DOI

Heterogeneous Scientific Foundation Model Collaboration

Zihao Li, Jiaru Zou, Feihao Fang, Xuying Ning, Mengting Ai, Tianxin Wei, Sirui Chen, Xiyuan Yang, Jingrui He ยท 2026

Agentic large language model systems have demonstrated strong capabilities. However, their reliance on language as the universal interface fundamentally limits their applicability to many real-world pโ€ฆ

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Computer Science Preprint PDF DOI

Multi-element Persuasion in Social Media Health Communication: Synergistic and Trade-off Effects

Weifeng Zhang, Jipeng Tan, Mengye Yang, Yong Min ยท 2026

Health messages on social media are typically constructed through combinations of source cues, appeals, frames, and evidence, which jointly shape communication and persuasive effects. However, prior rโ€ฆ

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Computer Science Preprint PDF DOI

Profiles of AI Dependency: A Latent Class Analysis of Filipino Students' Academic Competencies

Emerson Q. Fernando, Julius Ceazar G. Tolentino, Maria Anna D. Cruz, Jordan L. Salenga, Vernon Grace M. Maniago, Juvy C. Grume, Erika M. Pineda, Aileen P. De Leon, John Paul P. Miranda ยท 2026

The increasing dependency among Filipino college students on artificial intelligence (AI) poses concerns about the potential decline of fundamental academic competencies. This study examines the extenโ€ฆ

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Computer Science Preprint PDF DOI

Exploring the Adoption Intention in Using AI-Enabled Educational Tools Among Preservice Teachers in the Philippines: A Partial-Least Square Modeling

Vanessa B. Sibug, Emerson Q. Fernando, Almer B. Gamboa, Roque Francis B. Dianelo, Agnes R. Regala, Joseph Alexander Bansil, Jan Henry B. Sunga, Vernon Grace M. Maniago, John Paul P. Miranda ยท 2026

This study examines the factors influencing pre-service teachers' behavioral intention to use AI-enabled educational tools during their practicum, using the Unified Theory of Acceptance and Use of Tecโ€ฆ

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Computer Science Preprint PDF DOI

Bibliometric Mapping of AI-Supported Social Presence in Online Learning Environments: Trends, Collaboration, and Thematic Directions

Almer B. Gamboa, Erika M. Pineda, Rhiziel P. Manalese, Aileen P. De Leon, Vernon Grace M. Maniago, Jan Henry B. Sunga, Agnes R. Regala, Roque Francis B. Dianelo, John Paul P. Miranda ยท 2026

This study examines the development, influence, and collaboration patterns in AI-supported social presence research within online learning environments. Utilizing 59 open-access empirical studies fromโ€ฆ

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AI & Data Science Preprint PDF DOI

JI-ADF: Joint-Individual Learning with Adaptive Decision Fusion for Multimodal Skin Lesion Classification

Phan Nguyen, Dat Cao, Quang Hien Kha, Hien Chu, Minh H. N. Le, Trang Quoc Thao Pham, Nguyen Quoc Khanh Le ยท 2026

Skin lesion classification is essential for early dermatological diagnosis, yet many existing computer-aided systems rely primarily on dermoscopic images and underutilize the multimodal evidence routiโ€ฆ

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AI & Data Science Preprint PDF DOI

Investigating More Explainable and Partition-Free Compositionality Estimation for LLMs: A Rule-Generation Perspective

Ziyao Xu, Cong Wang, Houfeng Wang ยท 2026

Compositional generalization tests are often used to estimate the compositionality of LLMs. However, such tests have the following limitations: (1) they only focus on the output results without considโ€ฆ

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