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๐Ÿ” david i. august ๐Ÿ“‚ Computer Science
Showing 16491 results for "david i. august" in Computer Science
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I hope we don't do to trust what advertising has done to love

Jade Alglave ยท 2026

Advertising uses love to sell stuff, like nylons. It also uses the word "love" in trivialising ways -- do you "love" your oven? When I hear about trust in the context of AI, especially agentic, I hopeโ€ฆ

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Exploring Sparse Matrix Multiplication Kernels on the Cerebras CS-3

Milan Shah, Sheng Di, Michela Becchi ยท 2026

In recent years, novel AI accelerators have emerged as promising alternatives to GPU for AI model training and inference tasks. One such accelerator, the Cerebras CS-3, achieves strong performance on โ€ฆ

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WOOTdroid: Whole-system Online On-device Tracing for Android

Simon Althaus, Nikolaos Alexopoulos, Max Muhlhauser, Christian Reuter, Ephraim Zimmer ยท 2026

System auditing on Android faces two problems. First, existing syscall tracers lose events under load, silently overwriting entries faster than a user space reader can drain them. Second, security-relโ€ฆ

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Maximally Diverse Stable Matchings: Optimizing Arbitrary Institutional Objectives

Gergely Csaji, Zhaohong Sun ยท 2026

Stable matching theory is the foundation of centralized clearinghouses worldwide, from school choice programs to medical residency allocations. However, incorporating complex distributional goals-suchโ€ฆ

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A Generalisation of Goursat's Algorithm for Integration in Finite Terms

Sam Blake ยท 2026

We give a self-contained, modern exposition of \'Edouard Goursat's 1887 theorem on pseudo-elliptic integrals -- those integrals of the form $\int F(t)\,\d t/\sqrt{R(t)}$ with $R$ a cubic or quartic poโ€ฆ

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Position-Aware Drafting for Inference Acceleration in LLM-Based Generative List-Wise Recommendation

Jiaju Chen, Chongming Gao, Chenxiao Fan, Haoyan Liu, Qingpeng Cai, Peng Jiang, Xiangnan He ยท 2026

Large language model (LLM)-based generative list-wise recommendation has advanced rapidly, but decoding remains sequential and thus latency-prone. To accelerate inference without changing the target dโ€ฆ

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Towards an Ethical AI Curriculum: A Pan-African, Culturally Contextualized Framework for Primary and Secondary Education

Abidemi Kuburat Adedeji, Franklin Tchakounte, Sulaiman Oluwasegun Yusuff ยท 2026

Artificial intelligence (AI) is now embedded in educational, civic, and economic systems worldwide. For African primary and secondary education, this creates a double imperative: to prepare a young poโ€ฆ

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Libra: Accelerating Socket I/O via Programmable Selective Data Copying

Kairui Zhou, Shengkai Lin, Wei Zhang, Shizhen Zhao ยท 2026

Layer-7 (L7) proxies are critical to modern cloud-native systems, yet their performance is increasingly bottlenecked by copying entire payloads across the kernel-user boundary. Existing approaches redโ€ฆ

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I'm Fine, But My Voice Isn't: Cross-Modal Affective Dissonance Detection for Reflective Journaling

Sumin Lee ยท 2026

Digital journaling creates an authenticity gap: users consciously translate raw emotions into text, often sanitizing narratives even in private writing. We formalize this as Cross-Modal Affective Dissโ€ฆ

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SafeTune: Mitigating Data Poisoning in LLM Fine-Tuning for RTL Code Generation

Mahshid Rezakhani, Nowfel Mashnoor, Kimia Azar, Hadi Kamali ยท 2026

As large language models (LLMs) are increasingly fine-tuned for hardware tasks like RTL code generation, the scarcity of high-quality datasets often leads to the use of rapidly assembled or generated โ€ฆ

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End-to-End and Phase-Level Performance Optimization for Hyperledger Fabric

Pavan Sollu, Aniruddha Mukherjee, Divya Pulivarthi, S.R. Eshwar, Gugan Thoppe, Kshitij Pratihast, Tittu Varghese, Hrishikesh Nashikkar, Yogesh Simmhan ยท 2026

Hyperledger Fabric (HLF) is a modular, permissioned blockchain widely adopted in enterprise settings. Enhancing its throughput and latency remains challenging, as optimization decisions made in one phโ€ฆ

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Hypencoder Revisited: Reproducibility and Analysis of Non-Linear Scoring for First-Stage Retrieval

Arne Eichholtz, Yongkang Li, Jutte Vijverberg, Tobias Groot, Mohammad Aliannejadi ยท 2026

The Hypencoder, proposed by Killingback et al., is a retrieval framework that replaces the fixed inner-product scoring function used in standard bi-encoders with a query-specific neural network (the $โ€ฆ

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Weighted Emulators with Local Heaviest Edges Stretch for Undirected Graphs

Liam Roditty, Ariel Sapir ยท 2026

We introduce a generalized family of $\left( 2\cdot \left\lfloor \frac{k}{2} \right\rfloor-1, 2\cdot \left\lceil \frac{k}{2} \right\rceil \cdot W_{1} +\max\left\{0,2\cdot\left(\left\lceil\frac{k}{2}\rโ€ฆ

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Catching the Fly: Practical Challenges in Making Blockchain FlyClient Real

Pericle Perazzo, Dario Capecchi ยท 2026

FlyClient is a lightweight blockchain verification protocol that enables proof-of-work validation using minimal data, making it ideal for resource-constrained environments like mobile wallets, Interneโ€ฆ

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On (In)approximability of MaxMin Independent Set Reconfiguration

Hung P. Hoang, Naoto Ohsaka, Rin Saito, Yuma Tamura ยท 2026

In the Independent Set Reconfiguration problem under the Token Addition/Removal rule, given a graph $G$ and two independent sets $I$ and $J$ of $G$, we want to transform $I$ into $J$ by adding and remโ€ฆ

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Recommendations for Efficient and Responsible LLM Adoption within Industrial Software Development

Krishna Ronanki, Beatriz Cabrero-Daniel, Tomas Herda, Stefan Sitkovich, Jennifer Horkoff, Christian Berger ยท 2026

Context: Large language models (LLMs) are observed to have a significant positive impact on various software engineering (SE) activities. With improved accessibility, the adoption of powerful LLMs in โ€ฆ

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DUAL-BLADE: Dual-Path NVMe-Direct KV-Cache Offloading for Edge LLM Inference

Bodon Jeong, Hongsu Byun, Youngjae Kim, Weikuan Yu, Kyungkeun Lee, Jihoon Yang, Sungyong Park ยท 2026

The increasing deployment of Large Language Model (LLM) inference on edge AI systems demands efficient execution under tight memory budgets. A key challenge arises from Key-Value (KV) caches, which ofโ€ฆ

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PRAG: End-to-End Privacy-Preserving Retrieval-Augmented Generation

Zhijun Li, Minghui Xu, Huayi Qi, Wenxuan Yu, Tingchuang Zhang, Qiao Zhang, GuangYong Shang, Zhen Ma, Xiuzhen Cheng ยท 2026

Retrieval-Augmented Generation (RAG) is essential for enhancing Large Language Models (LLMs) with external knowledge, but its reliance on cloud environments exposes sensitive data to privacy risks. Exโ€ฆ

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Beyond Accuracy: LLM Variability in Evidence Screening for Software Engineering SLRs

Gilberto Sussumu Hida, Danilo Monteiro Ribeiro, Erika Yahata ยท 2026

Context: Study screening in systematic literature reviews is costly, inconsistency-prone, and risk-asymmetric, since false negatives can compromise validity. Despite rapid uptake of Large Language Modโ€ฆ

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Do E-Scooter Speed Governance Policies Reduce Harsh Acceleration and Deceleration? Evidence from 19.5 Million Trips Around a Regulatory Ban

Seongjin Choi, Sunbin Yoo, Sugie Lee ยท 2026

Do e-scooter speed governance policies yield behavioral safety gains beyond the mechanical cap they impose? A firmware ceiling mechanically prevents speeding, but whether the same riders also generateโ€ฆ

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