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Please consider supporting Sofia's Camera Club ride for pancreatic cancer up Cypress https://cypresschallenge.ca/team/scc This will be our 8th year. @… join…

A roundup of VLSI conference 2025, including the use of digital twins for design exploration, DRAM beyond 1x nm nodes, Intel's 18A process vs. TSMC, and more (SemiAnalysis)
https://semianalysis.com/2025/07/21/vlsi2025/

Intel 18A Details & Cost, Future of DRAM 4F2 vs 3D, Backside Power Adoption (or Not), China’s FlipFET, Digital Twins from Atoms to Fabs, and More
Long time readers will recall that SemiAnalysis covers more than just datacenters and AMD. Today we’re back to semiconductors with a tech-focused roundup of the best from this year’s VLSI conferenc…

Using Modular Arithmetic Optimized Neural Networks To Crack Affine Cryptographic Schemes Efficiently
Vanja Stojanovi\'c, \v{Z}iga Lesar, CIril Bohak
https://arxiv.org/abs/2507.14229

Using Modular Arithmetic Optimized Neural Networks To Crack Affine Cryptographic Schemes Efficiently
We investigate the cryptanalysis of affine ciphers using a hybrid neural network architecture that combines modular arithmetic-aware and statistical feature-based learning. Inspired by recent advances in interpretable neural networks for modular arithmetic and neural cryptanalysis of classical ciphers, our approach integrates a modular branch that processes raw ciphertext sequences and a statistical branch that leverages letter frequency features. Experiments on datasets derived from natural En…

Coker: We can’t have economic prosperity or national security without cybersecurity https://therecord.media/coker-interview-no-economic-security-without-cybersecurity

Optimal Planning for Multi-Robot Simultaneous Area and Line Coverage Using Hierarchical Cyclic Merging Regulation
Tianyuan Zheng, Jingang Yi, Kaiyan Yu
https://arxiv.org/abs/2508.04981

Optimal Planning for Multi-Robot Simultaneous Area and Line Coverage Using Hierarchical Cyclic Merging Regulation
The double coverage problem focuses on determining efficient, collision-free routes for multiple robots to simultaneously cover linear features (e.g., surface cracks or road routes) and survey areas (e.g., parking lots or local regions) in known environments. In these problems, each robot carries two functional roles: service (linear feature footprint coverage) and exploration (complete area coverage). Service has a smaller operational footprint but incurs higher costs (e.g., time) compared to …

Mapping feedback signatures in 3C 297: A quasar-host merger at Cosmic Noon
Chetna Duggal, Christopher P. O'Dea, Stefi A. Baum, John Jiwa, Grant Tremblay, Marco Chiaberge, George Miley, Carlo Stanghellini, William Sparks
https://arxiv.org/abs/2508.11926

Mapping feedback signatures in 3C 297: A quasar-host merger at Cosmic Noon
We present a study of quasar host galaxy 3C 297 which is home to a powerful bent-jet radio source suggesting vigorous interaction with a dense ISM and/or jet precession. Archival HST imaging showed interestingly perturbed morphology of the host with a bright ~30 kpc arc feature, extended filamentary structure of line-emitting gas and clumpy blue excess emission co-spatial with the radio hotspots. Our VLT/SINFONI integral-field observations reveal complex, spatially-resolved Hα+[NII] emission i…

Generative AI for Cybersecurity of Energy Management Systems: Methods, Challenges, and Future Directions
Aydin Zaboli, Junho Hong
https://arxiv.org/abs/2508.10044 https://

Generative AI for Cybersecurity of Energy Management Systems: Methods, Challenges, and Future Directions
This paper elaborates on an extensive security framework specifically designed for energy management systems (EMSs), which effectively tackles the dynamic environment of cybersecurity vulnerabilities and/or system problems (SPs), accomplished through the incorporation of novel methodologies. A comprehensive multi-point attack/error model is initially proposed to systematically identify vulnerabilities throughout the entire EMS data processing pipeline, including post state estimation (SE) steal…

AI-Based Software Vulnerability Detection: A Systematic Literature Review
Samiha Shimmi, Hamed Okhravi, Mona Rahimi
https://arxiv.org/abs/2506.10280 https:…

AI-Based Software Vulnerability Detection: A Systematic Literature Review
Software vulnerabilities in source code pose serious cybersecurity risks, prompting a shift from traditional detection methods (e.g., static analysis, rule-based matching) to AI-driven approaches. This study presents a systematic review of software vulnerability detection (SVD) research from 2018 to 2023, offering a comprehensive taxonomy of techniques, feature representations, and embedding methods. Our analysis reveals that 91% of studies use AI-based methods, with graph-based models being th…

This https://arxiv.org/abs/2412.03824 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

Towards Data Governance of Frontier AI Models
Data is essential to train and fine-tune today's frontier artificial intelligence (AI) models and to develop future ones. To date, academic, legal, and regulatory work has primarily addressed how data can directly harm consumers and creators, such as through privacy breaches, copyright infringements, and bias and discrimination. Our work, instead, focuses on the comparatively neglected question of how data can enable new governance capacities for frontier AI models. This approach for "frontier …