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๐Ÿ” edith hemaspaandra ๐Ÿ“‚ Computer Science
Showing 1292 results for "edith hemaspaandra" in Computer Science
Computer Science Preprint PDF DOI

How Generative AI Disrupts Search: An Empirical Study of Google Search, Gemini, and AI Overviews

Riley Grossman, Songjiang Liu, Michael K. Chen, Mike Smith, Cristian Borcea, Yi Chen ยท 2026

Generative AI is being increasingly integrated into web search for the convenience it provides users. In this work, we aim to understand how generative AI disrupts web search by retrieving and presentโ€ฆ

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lpviz: Interactive Linear Programming Visualization

Evan Grand, Michael Klamkin ยท 2026

This paper presents lpviz, a browser-based visualization tool for linear programming. lpviz is deeply interactive, offering an intuitive interface where users can directly draw and edit the feasible rโ€ฆ

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To Diff or Not to Diff? Structure-Aware and Adaptive Output Formats for Efficient LLM-based Code Editing

Wei Cheng, Yongchang Cao, Chen Shen, Binhua Li, Jue Chen, Yongbin Li, Wei Hu ยท 2026

Large Language Models (LLMs) are increasingly used for code editing, yet the prevalent full-code generation paradigm suffers from severe efficiency bottlenecks, posing challenges for interactive codinโ€ฆ

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Few-Shot Accent Synthesis for ASR with LLM-Guided Phoneme Editing

Yurii Halychanskyi, Nimet Beyza Bozdag, Mark Hasegawa-Johnson, Dilek Hakkani-Tur, Volodymyr Kindratenko ยท 2026

Accented automatic speech recognition (ASR) often degrades due to the limited availability of accented training data. Prior work has explored accent modeling in low-resource settings, but existing appโ€ฆ

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When Model Editing Meets Service Evolution: A Knowledge-Update Perspective for Service Recommendation

Guodong Fan, Cuiyun Gao, Chun Yong Chong, Lu Zhang, Jing Li, Jinglin Zhang, Shizhan Chen ยท 2026

The rapid evolution of software services poses substantial challenges to the design and implementation of effective recommendation systems. Traditional service recommendation approaches often rely on 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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Can Code Evaluation Metrics Detect Code Plagiarism?

Fahad Ebrahim, Mike Joy (The University of Warwick) ยท 2026

Source Code Plagiarism Detection (SCPD) plays an important role in maintaining fairness and academic integrity in software engineering education. Code Evaluation Metrics (CEMs) are developed for assesโ€ฆ

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SAFEdit: Does Multi-Agent Decomposition Resolve the Reliability Challenges of Instructed Code Editing?

Noam Tarshish, Nofar Selouk, Daniel Hodisan, Bar Ezra Gafniel, Yuval Elovici, Asaf Shabtai, Eliya Nachmani ยท 2026

Instructed code editing is a significant challenge for large language models (LLMs). On the EditBench benchmark, 39 of 40 evaluated models obtain a task success rate (TSR) below 60 percent, highlightiโ€ฆ

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Clustering Permutations under the Ulam Metric: A Parameterized Complexity Study

Tian Bai, Fedor V. Fomin, Petr A. Golovach, Yash Hiren More, Simon Wietheger ยท 2026

Rank aggregation seeks a representative permutation for a collection of rankings and plays a central role in areas such as social choice, information retrieval, and computational biology. Two fundamenโ€ฆ

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Leveraging LLMs for Multi-File DSL Code Generation: An Industrial Case Study

Sivajeet Chand, Kevin Nguyen, Peter Kuntz, Alexander Pretschner ยท 2026

Large language models (LLMs) perform strongly on general-purpose code generation, yet their applicability to enterprise domain-specific languages (DSLs) remains underexplored, especially for repositorโ€ฆ

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Prox-E: Fine-Grained 3D Shape Editing via Primitive-Based Abstractions

Etai Sella, Hao Phung, Nitay Amiel, Or Litany, Or Patashnik, Hadar Averbuch-Elor ยท 2026

Text-based 2D image editing models have recently reached an impressive level of maturity, motivating a growing body of work that heavily depends on these models to drive 3D edits. While effective for โ€ฆ

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Code for All: Educational Applications of the "Vibe Coding" Hackathon in Programming Education across All Skill Levels

Ashley J. Chen, Yijia Cao, Minghao Shao, Ramesh Karri, Muhammad Shafique ยท 2026

The emergence of large language models has enabled vibe coding, a natural language approach to programming in which users describe intent and AI generates or revises code, potentially broadening accesโ€ฆ

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RAG-Reflect: Agentic Retrieval-Augmented Generation with Reflections for Comment-Driven Code Maintenance on Stack Overflow

Mehedi Hasan Shanto, Muhammad Asaduzzaman, Alioune Ngom ยท 2026

User comments on online programming platforms such as Stack Overflow play a vital role in maintaining the correctness and relevance of shared code examples. However, the majority of comments express gโ€ฆ

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How Many Visual Levers Drive Urban Perception? Interventional Counterfactuals via Multiple Localised Edits

Jason Tang, Stephen Law ยท 2026

Street-view perception models predict subjective attributes such as safety at scale, but remain correlational: they do not identify which localized visual changes would plausibly shift human judgementโ€ฆ

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AutoRISE: Agent-Driven Strategy Evolution for Red-Teaming Large Language Models

Tanmay Gautam, Alireza Bahramali, Sandeep Atluri ยท 2026

Automated red-teaming methods for large language models typically optimize attack prompts within a fixed, human-designed strategy, leaving the attack strategy itself unchanged. We instead optimize theโ€ฆ

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Self-Aware Vector Embeddings for Retrieval-Augmented Generation: A Neuroscience-Inspired Framework for Temporal, Confidence-Weighted, and Relational Knowledge

Naizhong Xu ยท 2026

Modern retrieval-augmented generation (RAG) systems treat vector embeddings as static, context-free artifacts: an embedding has no notion of when it was created, how trustworthy its source is, or whicโ€ฆ

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AttentionBender: Manipulating Cross-Attention in Video Diffusion Transformers as a Creative Probe

Adam Cole, Mick Grierson ยท 2026

We present AttentionBender, a tool that manipulates cross-attention in Video Diffusion Transformers to help artists probe the internal mechanics of black-box video generation. While generative outputsโ€ฆ

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PlayCoder: Making LLM-Generated GUI Code Playable

Zhiyuan Peng, Wei Tao, Xin Yin, Chenhao Ying, Yuan Luo, Yiwen Guo ยท 2026

Large language models (LLMs) have achieved strong results in code generation, but their ability to generate GUI applications, especially games, remains insufficiently studied. Existing benchmarks mainโ€ฆ

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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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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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