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๐Ÿ” keefer rowan ๐Ÿ“‚ Computer Science
Showing 1954 results for "keefer rowan" in Computer Science
Computer Science Preprint PDF DOI

Feature-Centric Methodology for Analyzing Cross-Chain NFT Migration Compatibility

Mohd Sameen Chishti, Damilare Peter Oyinloye, Jingyue Li ยท 2026

Cross-chain NFT migration refers to the process of transferring digital assets along with their associated functionalities and guarantees between distinct blockchain platforms. However, architectural โ€ฆ

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Which Types of Heterogeneity Matter for Root Cause Localization in Microservice Systems ?

Runzhou Wang, Shenglin Zhang, Wenwei Gu, Yongxin Zhao, Chenyu Zhao, Dan Pei, Yuxuan Chen, Yangyuxin Huang ยท 2026

Microservice root cause localization is fundamentally challenged by the inherent heterogeneity of cloud-native systems, which encompasses diverse observability data and multiple system entities. Existโ€ฆ

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Hands-on PDC in Undergraduate Computing Education

Hala ElAarag, Anas Gamal Aly ยท 2026

Parallel and Distributed Computing (PDC) is a critical yet conceptually challenging area of the undergraduate computer science curriculum. While students often encounter these concepts in theory, few โ€ฆ

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EOS-Bench: A Comprehensive Benchmark for Earth Observation Satellite Scheduling

Qian Yin, Jiaxing Li, Jiaqi Cheng, Qizhang Luo, Annalisa Riccardi, Abhijit Chatterjee, Rafael Vazquez, Carlo Novara, Michalis Mavrovouniotis, Ponnuthurai Nagaratnam Suganthan, Shengzhou Bai, Xiaoxuan Hu, Lining Xing, Ming Xu, Shuang Li, Zixuan Zheng, Xin Shen, Xiaoyu Chen, Yi Gu, Yanjie Song, Witold Pedrycz, Evan L. Kramer, Laio Oriel Seman, Cletah Shoko, Guohua Wu, Xinwei Wang ยท 2026

Earth observation satellite imaging scheduling is a challenging NP-hard combinatorial optimisation problem central to space mission operations. While next-generation agile Earth observation satellitesโ€ฆ

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Computer Science Preprint PDF DOI

Assistants, Not Architects: The Role of LLMs in Networked Systems Design

Pratyush Sahu, Rahul Bothra, Venkat Arun, Brighten Godfrey, Akshay Narayan, Ahmed Saeed ยท 2026

Designing the architecture of modern networked systems requires navigating a large, combinatorial space of hardware, systems, and configuration choices with complex cross-layer interactions. Architectโ€ฆ

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GLIER: Generative Legal Inference and Evidence Ranking for Legal Case Retrieval

Minghan Li, Tianrui Lv, Chao Zhang, Guodong Zhou ยท 2026

The semantic gap between colloquial user queries and professional legal documents presents a fundamental challenge in Legal Case Retrieval (LCR). Existing dense retrieval methods typically treat LCR aโ€ฆ

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Designing a Visualization Atlas: Lessons & Reflections from The UK Co-Benefits Atlas for Climate Mitigation

Jinrui Wang, Alexis Pister, Sian Phillips, Sarah Bissett, Ruaidhri Higgins-Lavery, Clare Wharmby, Andrew Sudmant, Uta Hinrichs, Benjamin Bach ยท 2026

This paper reports on the process of designing the UK Co-Benefits Atlas, which communicates and publicizes data for climate mitigation. Visualization atlases -- an emerging type of platform to make daโ€ฆ

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Computer Science Preprint PDF DOI

T2S-Metrics: Unified Library for Evaluating SPARQL Queries Generated From Natural Language

Yousouf Taghzouti (ICN, WIMMICS, Laboratoire I3S - SPARKS), Tao Jiang (ICN), Camille Juigne (WIMMICS, Laboratoire I3S - SPARKS), Benjamin Navet (ICN, WIMMICS, Laboratoire I3S - SPARKS), Fabien Gandon (WIMMICS, Laboratoire I3S - SPARKS), Franck Michel (Laboratoire I3S - SPARKS, WIMMICS), Louis-Felix Nothias (ICN) ยท 2026

The evaluation of Question Answering (QA) systems over Knowledge Graphs has historically suffered from fragmentation, inconsistency, and limited reproducibility. While significant progress has been maโ€ฆ

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Regulating Artificial Intimacy: From Locks and Blocks to Relational Accountability

Henry Fraser, Jessica M. Szczuka, Raffaele F. Ciriello ยท 2026

A series of high-profile tragedies involving companion chatbots has triggered an unusually rapid regulatory response. Several jurisdictions, including Australia, California, and New York, have introduโ€ฆ

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RankUp: Towards High-rank Representations for Large Scale Advertising Recommender Systems

Jin Chen, Shangyu Zhang, Bin Hu, Chao Zhou, Junwei Pan, Gengsheng Xue, Wentao Ning, Gengyu Weng, Wang Zheng, Shaohua Liu, Zeen Xu, Chengyuan Mai, Shijie Quan, Tingyu Jiang, Lifeng Wang, Shudong Huang, Chengguo Yin, Haijie Gu, Jie Jiang ยท 2026

The scaling laws for recommender systems have been increasingly validated, where MetaFormer-based architectures consistently benefit from increased model depth, hidden dimensionality, and user behavioโ€ฆ

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Towards Deep Encrypted Training: Low-Latency, Memory-Efficient, and High-Throughput Inference for Privacy-Preserving Neural Networks

Nges Brian Njungle, Eric Jahns, Michel A. Kinsy ยท 2026

Privacy-preserving machine learning (PPML) has become increasingly important in applications where sensitive data must remain confidential. Homomorphic Encryption (HE) enables computation directly on โ€ฆ

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New Kids: An Architecture and Performance Investigation of Second-Generation Serverless Platforms

Trever Schirmer, Aris Wiegand, Lucca di Benedetto, Linus Gustafsson, Natalie Carl, Tobias Pfandzelter, David Bermbach ยท 2026

With the ever-increasing usage of serverless computing in both industry and academia, it is essential to understand the mechanisms that power the underlying platforms. As serverless is more than ten yโ€ฆ

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Sample Is Feature: Beyond Item-Level, Toward Sample-Level Tokens for Unified Large Recommender Models

Shuli Wang, Junwei Yin, Changhao Li, Senjie Kou, Chi Wang, Yinqiu Huang, Yinhua Zhu, Haitao Wang, Xingxing Wang ยท 2026

Scaling industrial recommender models has followed two parallel paradigms: \textbf{sample information scaling} -- enriching the information content of each training sample through deeper and longer beโ€ฆ

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Wave-Based Dispatch for Circuit Cutting in Hybrid HPC--Quantum Systems

Ricard S. Garcia-Raigada, Josep Jorba, Sergio Iserte ยท 2026

Hybrid High-performance Computing (HPC)-quantum workloads based on circuit cutting decompose large quantum circuits into independent fragments, but existing frameworks tightly couple cutting logic to โ€ฆ

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Comprehension Debt in GenAI-Assisted Software Engineering Projects

Muhammad Ovais Ahmad ยท 2026

Generative Artificial Intelligence (GenAI) tools (e.g., ChatGPT, Calude) have rapidly become integral to software development. These tools are especially attractive to students, as they can reduce cogโ€ฆ

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Automated SVA Generation with LLMs

Lik Tung Fu, Qihang Wang, Shaokai Ren, Mengli Zhang, Sichao Yang, Jun Liu, Xi Wang ยท 2026

Functional verification remains a dominant cost in modern IC development, and SystemVerilog Assertions (SVAs) are critical for simulation-based monitoring and formal property checking. However, writinโ€ฆ

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LLMs for Qualitative Data Analysis Fail on Security-specificComments in Human Experiments

Maria Camporese, Fabio Massacci, Yuanjun Gong ยท 2026

[Background:] Thematic analysis of free-text justifications in human experiments provides significant qualitative insights. Yet, it is costly because reliable annotations require multiple domain experโ€ฆ

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Enhanced Self-Learning with Epistemologically-Informed LLM Dialogue

Yi-Fan Cao, Kento Shigyo, Yitong Gu, Xiyuan Wang, Weijia Liu, Yang Wang, David Gotz, Zhilan Zhou, Huamin Qu ยท 2026

Large Language Models (LLMs) have advanced self-learning tools, enabling more personalized interactions. However, learners struggle to engage in meaningful dialogue and process complex information. Toโ€ฆ

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Confidence Without Competence in AI-Assisted Knowledge Work

Elena Eleftheriou, George Pallis, Marios Constantinides ยท 2026

Large Language Models (LLMs) are widely used by students, yet their tendency to provide fast and complete answers may discourage reflection and foster overconfidence. We examined how alternative LLM iโ€ฆ

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Intent Lenses: Inferring Capture-Time Intent to Transform Opportunistic Photo Captures into Structured Visual Notes

Ashwin Ram, Aeneas Leon Sommer, Martin Schmitz, Jurgen Steimle ยท 2026

Opportunistic photo capture (e.g., slides, exhibits, or artifacts) is a common strategy for preserving information encountered in information-rich environments for later revisitation. While fast and mโ€ฆ

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