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Showing 182110 results for "program development"
Computer Science Preprint PDF DOI

Suffix Random Access via Function Inversion: A Key for Asymmetric Streaming String Algorithms

Panagiotis Charalampopoulos, Taha El Ghazi, Jonas Ellert, Pawe{l} Gawrychowski, Tatiana Starikovskaya ยท 2026

Many string processing problems can be phrased in the streaming setting, where the input arrives symbol by symbol and we have sublinear working space. The area of streaming algorithms for string proceโ€ฆ

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Physics Preprint PDF DOI

Articulatory movements influence electromagnetic wave transmission through the vocal tract

Remi Blandin, Martin Laabs, Rudolf von Bunau, Bryn Lloyd, Silvia Farcito, Denys Nikolayev, Gabriela Hossu, Peter Birkholz, Dirk Plettemeier ยท 2026

This study experimentally validates a numerical model of electromagnetic propagation through the human head during the pronunciation of different vowels, with the goal of improving our understanding oโ€ฆ

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AI & Data Science Preprint PDF DOI

Scalable Memristive-Friendly Reservoir Computing for Time Series Classification

Cosku Can Horuz, Andrea Ceni, Claudio Gallicchio, Sebastian Otte ยท 2026

Memristive devices present a promising foundation for next-generation information processing by combining memory and computation within a single physical substrate. This unique characteristic enables โ€ฆ

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Computer Science Preprint PDF DOI

DebugRepair: Enhancing LLM-Based Automated Program Repair via Self-Directed Debugging

Linhao Wu, Yifei Pei, Zhen Yang, Kainan Li, Zhonghang Lu, Hao Tan, Xiran Lyu, Jia Li, Yizhou Chen, Pengyu Xue, Kunwu Zheng, Dan Hao ยท 2026

Automated Program Repair (APR) has benefited from the code understanding and generation capabilities of Large Language Models (LLMs). Existing feedback-based APR methods iteratively refine candidate pโ€ฆ

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AI & Data Science Preprint PDF DOI

Towards a Linguistic Evaluation of Narratives: A Quantitative Stylistic Framework

Alessandro Maisto ยท 2026

The evaluation of narrative quality remains a complex challenge, as it involves subjective factors such as plot, character development, and emotional impact. This work proposes a quantitative approachโ€ฆ

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Computer Science Preprint PDF DOI

BONSAI: A Mixed-Initiative Workspace for Human-AI Co-Development of Visual Analytics Applications

Thilo Spinner, Matthias Miller, Fabian Sperrle-Roth, Mennatallah El-Assady ยท 2026

Developing Visual Analytics (VA) applications requires integrating complex machine learning models with expressive interactive interfaces. Developers face a stark trade-off: building tightly-coupled mโ€ฆ

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AI & Data Science Preprint PDF DOI

UAF: A Unified Audio Front-end LLM for Full-Duplex Speech Interaction

Yadong Li, Guoxin Wu, Haiping Hou, Biye Li ยท 2026

Full-duplex speech interaction, as the most natural and intuitive mode of human communication, is driving artificial intelligence toward more human-like conversational systems. Traditional cascaded spโ€ฆ

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Computer Science Preprint PDF DOI

Audio Spoof Detection with GaborNet

Waldek Maciejko ยท 2026

An direction of development in the extraction of features from audio signals is based on processing raw samples in the time domain. Such an approach appears to be effective, especially in the era of nโ€ฆ

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Computer Science Preprint PDF DOI

Cascaded Code Editing: Large-Small Model Collaboration for Effective and Efficient Code Editing

Chaozheng Wang, Zezhou Yang, Shuzheng Gao, Cuiyun Gao, Zongjie Li, Yichen Li, Ting Peng, Hailiang Huang, Yuetang Deng, Michael R. Lyu ยท 2026

Code editing constitutes a fundamental practice in software development, wherein developers modify existing codebases according to natural language requirements. Accurate code editing necessitates a cโ€ฆ

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Computer Science Preprint PDF DOI

sumo3Dviz: A three dimensional traffic visualisation

Kevin Riehl, Julius Schlapbach, Anastasios Kouvelas, Michail A. Makridis ยท 2026

Traffic microsimulation software such as SUMO generate rich spatio-temporal data describing individual vehicle movements, interactions, and support the development of control strategies. While numericโ€ฆ

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Economics & Finance Preprint PDF DOI

A rapid evaluation of Australia's COVID-era apprentice wage subsidy programs

Peter Bowers, Patrick Rehill, Ethan Slaven ยท 2026

In the midst of the COVID-19 pandemic in 2020, the Australian Government launched two programs to incentivise new apprentices to start and complete apprenticeships -- the Boosting Apprenticeship Commeโ€ฆ

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AI & Data Science Preprint PDF DOI

RL-ABC: Reinforcement Learning for Accelerator Beamline Control

Anwar Ibrahim, Fedor Ratnikov, Maxim Kaledin, Alexey Petrenko, Denis Derkach ยท 2026

Particle accelerator beamline optimization is a high-dimensional control problem traditionally requiring significant expert intervention. We present RLABC (Reinforcement Learning for Accelerator Beamlโ€ฆ

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Computer Science Preprint PDF DOI

Towards More Empathic Programming Environments: An Experimental Empathic AI-Enhanced IDE

Justin Rainier Go, Kurt Christian Andaya, Roemer Gabriel Caliboso, Aaron Daniel Go, Jocelynn Cu ยท 2026

As generative AI becomes integral to software development, the risk of over-reliance and diminished critical thinking grows. This study introduces "Ceci," our Caring Empathic C IDE designed to supportโ€ฆ

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AI & Data Science Preprint PDF DOI

Construction of Knowledge Graph based on Language Model

Qiubai Zhu, Qingwang Wang, Haibin Yuan, Wei Chen, Tao Shen ยท 2026

Knowledge Graph (KG) can effectively integrate valuable information from massive data, and thus has been rapidly developed and widely used in many fields. Traditional KG construction methods rely on mโ€ฆ

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AI & Data Science Preprint PDF DOI

KD-Judge: A Knowledge-Driven Automated Judge Framework for Functional Fitness Movements on Edge Devices

Shaibal Saha, Fan Li, Yunge Li, Arun Iyengar, Lucas Alves, Lanyu Xu ยท 2026

Functional fitness movements are widely used in training, competition, and health-oriented exercise programs, yet consistently enforcing repetition (rep) standards remains challenging due to subjectivโ€ฆ

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Physics Preprint PDF DOI

Closing the Loop: Deploying Auto-Generating Digital Twins for Particle Accelerators

A. D. Brynes, M. King, K. R. L. Baker, R. Banerjee, R. Clarke, D. J. Dunning, J. K. Jones, M. Leputa, A. E. Pollard, M. Romanovschi, M. Shaw, N. Ziyan ยท 2026

The simulation of a physical system in a virtual replica, known as a digital twin, is a useful way to interrogate the system non-invasively, providing the ability to perform predictive maintenance andโ€ฆ

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Computer Science Preprint PDF DOI

MUCOCO: Automated Consistency Testing of Code LLMs

Chua Jin Chou, Khant That Lwin, Ezekiel Soremekun ยท 2026

Code LLMs often portray inconsistent program behaviors. Developers typically employ benchmarks to assess Code LLMs, but most benchmarks are hand-crafted, static and do not target consistency property.โ€ฆ

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Engineering Preprint PDF DOI

Reducing the Offline-Streaming Gap for Unified ASR Transducer with Consistency Regularization

Andrei Andrusenko, Vladimir Bataev, Lilit Grigoryan, Nune Tadevosyan, Vitaly Lavrukhin, Boris Ginsburg ยท 2026

Unification of automatic speech recognition (ASR) systems reduces development and maintenance costs, but training a single model to perform well in both offline and low-latency streaming settings remaโ€ฆ

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AI & Data Science Preprint PDF DOI

Evaluation of Winning Solutions of 2025 Low Power Computer Vision Challenge

Zihao Ye, Yung-Hsiang Lu, Xiao Hu, Shuai Zhang, Taotao Jing, Xin Li, Zhen Yao, Bo Lang, Zhihao Zheng, Seungmin Oh, Hankyul Kang, Seunghun Kang, Jongbin Ryu, Kexin Chen, Yuan Qi, George K Thiruvathukal, Mooi Choo Chuah ยท 2026

The IEEE Low-Power Computer Vision Challenge (LPCVC) aims to promote the development of efficient vision models for edge devices, balancing accuracy with constraints such as latency, memory capacity, โ€ฆ

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AI & Data Science Preprint PDF DOI

Learning Lifted Action Models from Unsupervised Visual Traces

Kai Xi, Stephen Gould, Sylvie Thiebaux ยท 2026

Efficient construction of models capturing the preconditions and effects of actions is essential for applying AI planning in real-world domains. Extensive prior work has explored learning such models โ€ฆ

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