arXiv:2602.04035v1 Announce Type: new Abstract: As data-intensive applications increasingly strain conventional computing systems, processing-in-memory (PIM) has emerged as a promising paradigm to alleviate the memory wall by minimizing data transfer between memory and processing units. This review presents the recent advances in both stateful and non-stateful logic techniques for PIM, focusing on emerging nonvolatile memory technologies such as resistive random-access memory (RRAM), phase-change memory (PCM), and magnetoresistive random-access memory (MRAM). Both experimentally demonstrated and simulated logic designs are […]

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arXiv:2301.00201v4 Announce Type: replace Abstract: We develop theory and methods that use the graph Laplacian to analyze the geometry of the underlying manifold of datasets. Our theory provides theoretical guarantees and explicit bounds on the functional forms of the graph Laplacian when it acts on functions defined close to singularities of the underlying manifold. We use these explicit bounds to develop tests for singularities and propose methods that can be used to estimate geometric properties of singularities in […]

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arXiv:2601.15423v1 Announce Type: new Abstract: We introduce Lattice, a hybrid sequential prediction system that conditionally activates learned behavioral structure using binary confidence gating. The system clusters behavior windows into behavioral archetypes and uses binary confidence gating to activate archetype-based scoring only when confidence exceeds a threshold, falling back to baseline predictions when uncertain. We validate Lattice on recommendation systems (MovieLens), scientific time-series (LIGO), and financial markets, using LSTM and transformer backbones. On MovieLens with LSTM, Lattice achieves +31.9% […]

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How a JSON or JSON-like language enables the next generation of safe human and AI-generated UIs Introduction In The Future of AI-Generated UI, I pointed out that the raw JavaScript generated by AI-generated code is a security problem, and the flexibility of JavaScript without a framework can result in hard-to-manage code. I argued that we need declarative, sandboxed formats like A2UI or a Computational DOM (cDOM) with JSON Pointer Regular Expressions (JPRX if), if we want to trust […]

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With the increasing adoption of EMV-based digital payment systems, ensuring compliance with privacy regulations (GDPR, PSD2, PCI DSS) has become essential. A critical challenge in regulatory-compliant payment transactions is the risk of transaction linkability, which can expose sensitive user data and violate privacy mandates. In this paper, I analyze the privacy vulnerabilities of EMV 2nd Gen payment protocols and propose an improved key agreement mechanism to enhance unlinkability and transaction security. The approach builds on the Blinded Diffie-Hellman […]

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:::info Authors: Dani Valevski Yaniv Leviathan Moab Arar Shlomi Fruchter ::: Table of Links ABSTRACT 1 INTRODUCTION 2 INTERACTIVE WORLD SIMULATION 3 GAMENGEN 3.1 DATA COLLECTION VIA AGENT PLAY 3.2 TRAINING THE GENERATIVE DIFFUSION MODEL 4 EXPERIMENTAL SETUP 4.1 AGENT TRAINING 4.2 GENERATIVE MODEL TRAINING 5 RESULTS 5.1 SIMULATION QUALITY 5.2 ABLATIONS 6 RELATED WORK 7 DISCUSSION, ACKNOWLEDGEMENTS AND REFERENCES ABSTRACT We present GameNGen, the first game engine powered entirely by a neural model that also enables real-time […]

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While distributed learning offers a new learning paradigm for distributed network with no central coordination, it is constrained by communication bottleneck between nodes. We develop a new event-triggered gossip framework for distributed learning to reduce inter-node communication overhead. The framework introduces an adaptive communication control mechanism that enables each node to autonomously decide in a fully decentralized fashion when to exchange model information with its neighbors based on local model deviations. We analyze the ergodic convergence of the […]

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arXiv:2602.07083v1 Announce Type: new Abstract: Structural modeling is a fundamental component of computational engineering science, in which even minor physical inconsistencies or specification violations may invalidate downstream simulations. The potential of large language models (LLMs) for automatic generation of modeling code has been demonstrated. However, non-executable or physically inconsistent outputs remain prevalent under stringent engineering constraints. A framework for physics-consistent automatic building modeling is therefore proposed, integrating domain knowledge construction, constraint-oriented model alignment, and verification-driven evaluation. CivilInstruct is […]

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About a month ago, Elon Musk boldly stated that “work will be optional” while discussing the future impact of AI on the workforce. While I assumed this was to evoke emotion in the general public, I felt stirred to explore this further. As adults, many of us are focused on just fulfilling basic needs of food, shelter, and safety. Psychologist Abraham Maslow’s hierarchy of needs states that we reach our full potential when we go beyond basic needs […]

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