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Showing 64015 results for "machine learning" in Computer Science
Computer Science Preprint PDF DOI

A Study on the Performance of Distributed Training of Data-driven CFD Simulations

Sergio Iserte, Alejandro Gonzalez-Barbera, Paloma Barreda, Krzysztof Rojek ยท 2026

Data-driven methods for computer simulations are blooming in many scientific areas. The traditional approach to simulating physical behaviors relies on solving partial differential equations (PDE). Siโ€ฆ

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Secret Stealing Attacks on Local LLM Fine-Tuning through Supply-Chain Model Code Backdoors

Zi Li, Tian Zhou, Wenze Li, Jingyu Hua, Yunlong Mao, Sheng Zhong ยท 2026

Local fine-tuning datasets routinely contain sensitive secrets such as API keys, personal identifiers, and financial records. Although ''local offline fine-tuning'' is often viewed as a privacy boundaโ€ฆ

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A Reproducibility Study of LLM-Based Query Reformulation

Amin Bigdeli, Radin Hamidi Rad, Hai Son Le, Mert Incesu, Negar Arabzadeh, Charles L. A. Clarke, Ebrahim Bagheri ยท 2026

Large Language Models (LLMs) are now widely used for query reformulation and expansion in Information Retrieval, with many studies reporting substantial effectiveness gains. However, these results areโ€ฆ

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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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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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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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Strongly Refuting Random CSP without Literals

Siu On Chan, Tommaso d'Orsi, Jeff Xu ยท 2026

Under what condition is a random constraint satisfaction problem hard to refute by the sum-of-squares (SoS) algorithm? A sufficient condition is t-wise uniformity, that is, each constraint has a t-wisโ€ฆ

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SQuadGen: Generating Simple Quad Layouts via Chart Distance Fields

Youkang Kong, Yang Liu, Yue Dong, Xin Tong, Heung-Yeung Shum ยท 2026

3D shapes from scanning, reconstruction, or AI-generated content often lack simple quad mesh layouts -- critical for efficient editing and modeling. Existing quad-remeshing techniques typically producโ€ฆ

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Toward Autonomous SOC Operations: End-to-End LLM Framework for Threat Detection, Query Generation, and Resolution in Security Operations

Md Hasan Saju, Akramul Azim ยท 2026

Security Operations Centers (SOCs) face mounting operational challenges. These challenges come from increasing threat volumes, heterogeneous SIEM platforms, and time-consuming manual triage workflows.โ€ฆ

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Cross-lingual Comparison of Research Funding Projects with Multilingual Sentence-BERT: Evidence from KAKENHI, NIH, NSF, and UKRI

Miki Kimura-Ida ยท 2026

Cross-national comparison of research funding projects is increasingly important for science policy and strategic planning, but language differences remain a major obstacle. In particular, KAKENHI proโ€ฆ

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Predicting Upcoming Stuttering Events from Three-Second Audio: Stratified Evaluation Reveals Severity-Selective Precursors, and the Model Deploys Fully On-Device

Nazar Kozak ยท 2026

Audio-based stuttering systems to date have been trained for detection -- what disfluency is present now -- leaving prediction, the capability needed for closed-loop intervention, unstudied at deployaโ€ฆ

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Fisher Markets with Approximately Optimal Bundles and the Need for a PCP Theorem for PPAD

Argyrios Deligkas, John Fearnley, Alexandros Hollender, Themistoklis Melissourgos ยท 2026

We study the problem of computing a competitive equilibrium with approximately optimal bundles in Fisher markets with separable piecewise-linear concave (SPLC) utility functions, meaning that every buโ€ฆ

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Unified Data Discovery across Query Modalities and User Intents

Tingting Wang, Shixun Huang, Zhifeng Bao, J. Shane Culpepper, Shazia Sadiq, Volkan Dedeoglu, Reza Arablouei ยท 2026

Data discovery - retrieving relevant tables from a data lake in response to user queries - is a fundamental building block for downstream analytics. In practice, data discovery must support different โ€ฆ

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Addressing the Reality Gap: A Three-Tension Framework for Agentic AI Adoption

Jason Fournier (Imagine Learning), Kacper {L}odzikowski (Adam Mickiewicz University, Poznan, Poland) ยท 2026

Generative AI has rapidly entered education through free consumer tools, outpacing the ability of schools and universities to respond. Now a new wave of more autonomous agentic AI systems--with the caโ€ฆ

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Upskilling with Generative AI: Practices and Challenges for Freelance Knowledge Workers

Kashif Imteyaz, Isabel Lopez, Nakul Rajpal, Hunjun Shin, Saiph Savage ยท 2026

Freelance workers must continually acquire new skills to remain competitive in online labor markets, yet they lack the organizational training, mentorship, and infrastructure available to traditional โ€ฆ

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Graphify: Automated Synthesis of Type-Safe Graph Backends via $O(S)$ GraphQL-to-Gremlin Transpilation

Johannes Graf ยท 2026

Graph databases offer unparalleled flexibility for managing interconnected data, yet the lack of strict schema enforcement often leads to runtime uncertainties and complex query development. This papeโ€ฆ

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Indirect Prompt Injection in the Wild: An Empirical Study of Prevalence, Techniques, and Objectives

Soheil Khodayari, Xuenan Zhang, Bhupendra Acharya, Giancarlo Pellegrino ยท 2026

As LLMs are increasingly integrated into systems that browse, retrieve, summarize, and act on web content, webpages have become an untrusted input vector for downstream model behavior. This enables siโ€ฆ

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A Gated Hybrid Contrastive Collaborative Filtering Recommendation

Eduardo Ferreira da Silva, Mayki dos Santos Oliveira, Joel Machado Pires, Denis Dantas Boaventura, Maycon Maciel Peixoto, Cassio Serafim Prazeres, Gustavo Bittencourt Figueiredo, Miriam Capretz, Frederico Araujo Durao ยท 2026

Recommender systems increasingly incorporate textual reviews to enrich user and item representations. However, most review-aware models remain optimized for rating prediction rather than ranking qualiโ€ฆ

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BLINC: Context-Specific Causal Learning for Automated RAN Configuration

Reshma Prasad, Michele Polese, Tommaso Melodia ยท 2026

Radio Access Network (RAN) configuration has traditionally required significant manual effort due to indirect causal dependencies between observable Key Performance Indicators (KPIs), and context-depeโ€ฆ

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Where did we fail? -- Reproducing build failures in embedded open source software

Han Fu, Andreas Ermedahl, Sigrid Eldh, Kristian Wiklund, Philipp Haller, Cyrille Artho ยท 2026

Due to hardware-software co-development in embedded systems, continuous integration (CI) builds frequently fail because of complex cross-compilation, board configurations, and toolchain constraints. Aโ€ฆ

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