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๐Ÿ” computer simulation ๐Ÿ“‚ Computer Science
Showing 291239 results for "computer simulation" in Computer Science
Computer Science Preprint PDF DOI

Hierarchical Long-Term Semantic Memory for LinkedIn's Hiring Agent

Zhentao Xu, Shangjing Zhang, Emir Poyraz, Yvonne Li, Ye Jin, Xie Lu, Xiaoyang Gu, Karthik Ramgopal, Praveen Kumar Bodigutla, Xiaofeng Wang ยท 2026

Large Language Model (LLM) agents are increasingly used in real-world products, where personalized and context-aware user interactions are essential. A central enabler of such capabilities is the agenโ€ฆ

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LLM-Assisted Empirical Software Engineering: Systematic Literature Review and Research Agenda

Victoria Gomes, Delaney Selb, Fabio Palomba, Rodrigo Spinola, David Lo ยท 2026

Context: Empirical Software Engineering (ESE) faces increasing challenges due to data scale, methodological complexity, and reproducibility concerns. Large Language Models (LLMs) have emerged as promiโ€ฆ

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Flashback: A Reversible Bilateral Run-Peeling Decomposition of Strings

Thomas Konstantinovsky, Gur Yaari ยท 2026

We introduce Flashback, a reversible string decomposition that repeatedly peels the maximal leading and trailing character runs from a sentinel-wrapped input, recording each pair as one bilateral tokeโ€ฆ

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Evergreen: Efficient Claim Verification for Semantic Aggregates

Alexander W. Lee, Benjamin Han, Shayak Sen, Sam Yeom, Ugur Cetintemel, Anupam Datta ยท 2026

With recent semantic query processing engines, semantic aggregation has become a primitive operator, enabling the reduction of a relation into a natural language aggregate using an LLM. However, the rโ€ฆ

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Hard-to-Sample Distributions from Robust Extractors

Farzan Byramji, Daniel M. Kane, Jackson Morris, Anthony Ostuni ยท 2026

We provide a unified method for constructing explicit distributions which are difficult for restricted models of computation to generate. Our constructions are based on a new notion of robust extractoโ€ฆ

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CacheRAG: A Semantic Caching System for Retrieval-Augmented Generation in Knowledge Graph Question Answering

Yushi Sun, Lei Chen ยท 2026

The integration of Large Language Models (LLMs) with Retrieval-Augmented Generation (RAG) has significantly advanced Knowledge Graph Question Answering (KGQA). However, existing LLM-driven KGQA systemโ€ฆ

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Fast and Faithful Edge Bundling using Spectral Sparsification

Xingjue Jiang, Seok-Hee Hong, Amyra Meidiana, Xianyuan Zeng ยท 2026

Edge bundling reduces the visual complexity of drawings of large and complex graphs by clustering "compatible" edges. However, it often introduces distortion by bundling "unrelated" edges, resulting iโ€ฆ

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Finite Functional Programming

Michael Arntzenius, Max Willsey ยท 2026

We unify functional and logic programming by treating predicatesas functions equipped with their support: the set of inputs whose output is nonzero. Datalog, for instance, is a language of finitely suโ€ฆ

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RAG-Enhanced Kernel-Based Heuristic Synthesis (RKHS): A Structured Methodology Using Large Language Models for Hardware Design

Shiva Ahir, Alex Doboli ยท 2026

Heuristic design upholds modern electronic design automation (EDA) tools, yet crafting effective placement, routing, and scheduling strategies entails substantial expertise. We study how large languagโ€ฆ

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AI Observability for Large Language Model Systems: A Multi-Layer Analysis of Monitoring Approaches from Confidence Calibration to Infrastructure Tracing

Twinkll Sisodia ยท 2026

The deployment of large language models (LLMs) in production environments has created an urgent need for observability systems that span the full stack -- from model internals to GPU kernels. Yet exisโ€ฆ

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Beyond Screenshots: Evaluating VLMs' Understanding of UI Animations

Chen Liang, Xirui Jiang, Naihao Deng, Eytan Adar, Anhong Guo ยท 2026

AI agents operating on user interfaces must understand how interfaces communicate state and feedback to act reliably. As a core communicative modality, animations are increasingly used in modern interโ€ฆ

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Ceci n'est pas une explication: Evaluating Explanation Failures as Explainability Pitfalls in Language Learning Systems

Ben Knight, Wm. Matthew Kennedy, James Edgell ยท 2026

AI-powered language learning tools increasingly provide instant, personalised feedback to millions of learners worldwide. However, this feedback can fail in ways that are difficult for learners--and eโ€ฆ

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ImproBR: Bug Report Improver Using LLMs

Emre Furkan Akyol, Mehmet Dedeler, Eray Tuzun ยท 2026

Bug tracking systems play a crucial role in software maintenance, yet developers frequently struggle with low-quality user-submitted reports that omit essential details such as Steps to Reproduce (S2Rโ€ฆ

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UCSC-NLP at SemEval-2026 Task 13: Multi-View Generalization and Diagnostic Analysis of Machine-Generated Code Detection

Kargi Chauhan, Sadiba Nusrat Nur ยท 2026

With the rapid growth of large language models for code generation, distinguishing between human-written and AI-generated code has become increasingly critical for academic integrity, hiring evaluatioโ€ฆ

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LLM-Guided Issue Generation from Uncovered Code Segments

Diany Pressato, Honghao Tan, Mariam Elmoazen, Shin Hwei Tan ยท 2026

Developers are increasingly overwhelmed by AI-generated issue reports that lack actionability and reproducibility, eroding trust in automated bug detection tools. In this paper, we present IssueSpecteโ€ฆ

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Multi-TRP Assisted UAV Detection in 3GPP 5G-Advanced ISAC Network

Neeraj Varshney, Steve Blandino, Jian Wang, Anuraag Bodi, Camillo Gentile, Nada Golmie ยท 2026

ISAC is currently being standardized within the 3GPP New Radio (NR) to enable cellular infrastructure to perform sensing using existing communication waveforms. While standardization is progressing, pโ€ฆ

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Human-Augmented Reality Interaction in Rebar Inspection

Mahsa Sanei, Fernando Moreu ยท 2026

Rebar inspection in reinforced concrete construction requires sustained awkward postures and complex mental mapping of two-dimensional drawings onto three-dimensional assemblies. This study evaluated โ€ฆ

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Application-Aware Twin-in-the-Loop Planning for Federated Split Learning over Wireless Edge Networks

Zihao Ding, Beining Wu, Jun Huang, Shiwen Mao ยท 2026

We investigate task-success-oriented resource allocation for federated split learning (FSL) at the wireless edge. In this setting, the server must jointly determine bandwidth, transmit power, split-laโ€ฆ

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AMMA: A Multi-Chiplet Memory-Centric Architecture for Low-Latency 1M Context Attention Serving

Zhongkai Yu, Haotian Ye, Chenyang Zhou, Ohm Rishabh Venkatachalam, Zaifeng Pan, Zhengding Hu, Junsung Kim, Won Woo Ro, Po-An Tsai, Shuyi Pei, Yangwook Kang, Yufei Ding ยท 2026

All current LLM serving systems place the GPU at the center, from production-level attention-FFN disaggregation to NVIDIA's Rubin GPU-LPU heterogeneous platform. Even academic PIM/PNM proposals still โ€ฆ

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SWE-Edit: Rethinking Code Editing for Efficient SWE-Agent

Yikai Zhang, Jiaxin Pei, Kenan Li, Maoquan Wang, Jin Pan, Yu Kang, Shengyu Fu, Elsie Nallipogu, Junjie Hu, Yufan Huang, Zijian Jin ยท 2026

Large language model agents have achieved remarkable progress on software engineering tasks, yet current approaches suffer from a fundamental context coupling problem: the standard code editing interfโ€ฆ

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