arXiv:2602.12398v1 Announce Type: new Abstract: Democracies are built upon secure and reliable voting systems. Electronic voting systems seek to replace ballot papers and boxes with computer hardware and software. Proposed electronic election schemes have been subjected to scrutiny, with researchers spotting inherent faults and weaknesses. Inspired by physical voting systems, we argue that any electronic voting system needs two essential properties: ballot secrecy and verifiability. These properties seemingly work against each other. An election scheme that is a […]

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Embedding models decide which passages an agent ever sees. NVIDIA released Nemotron 3 Embed model to work on that layer. It targets production-scale RAG, agentic retrieval, code retrieval, and agent memory. What is Nemotron 3 Embed? The model collection includes three open checkpoints. Nemotron-3-Embed-8B-BF16 is the accuracy-first option. Nemotron-3-Embed-1B-BF16 carries the same design into a smaller footprint. Nemotron-3-Embed-1B-NVFP4 is the Blackwell-optimized 4-bit path. All three are transformer encoders trained with bidirectional attention masking. The final embedding comes from […]

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Shem Albert Photo courtesy of Seyond Machines still struggle to see. Autonomous vehicles miscalculate distances. Delivery robots stumble on curbs. Industrial sensors fail when the weather turns harsh. Seyond addressed this gap by constructing a full spectrum of LiDAR sensors spanning from 0.01 meters to 500 meters, giving robots the visual acuity needed to operate safely among humans. Billy Evers, VP of Sales and Marketing for the Americas and APAC regions, states that Seyond offers what few others […]

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The Generative Pre-trained Transformer (GPT) series has changed artificial intelligence from a research curiosity to a mainstream tool, empowering innumerable interactions daily. The realization about the evolution of GPT versions over the years reveals how each one launched breakthroughs in language understanding and practical applications across industries. GPT Version Comparison Table Features Release Date Parameters Training Data Text Quality Capabilities Accessibility Architecture Improvements Safety & Alignment Use Cases Integration Languages Supported Pricing Plan GPT-1 June 2018 117M Books […]

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I’m Safiullah Korai, though many know me as Shahzaib. I’m a Software Engineer and full‑stack Flutter developer who started sharing my journey online not so long ago. Over time, by consistently documenting what I was learning and building, something interesting happened: my name began to show up. If you search Safiullah Korai on Google, you’ll see a knowledge panel, a quiet snapshot of my work and background. That small digital footprint now gives a strong first impression of credibility and […]

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Human mobility trajectories are widely studied in public health and social science, where different demographic groups exhibit significantly different mobility patterns. However, existing trajectory generation models rarely capture this heterogeneity because most trajectory datasets lack demographic labels. To address this gap in data, we propose ATLAS, a weakly supervised approach for demographic-conditioned trajectory generation using only (i) individual trajectories without demographic labels, (ii) region-level aggregated mobility features, and (iii) region-level demographic compositions from census data. ATLAS trains a […]

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arXiv:2602.18603v1 Announce Type: new Abstract: Corrections offer a natural modality for people to provide feedback to a robot, by (i) intervening in the robot’s behavior when they believe the robot is failing (or will fail) the task objectives and (ii) modifying the robot’s behavior to successfully fulfill the task. Each correction offers information on what the robot should and should not do, where the corrected behavior is more aligned with task objectives than the original behavior. Most prior […]

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arXiv:2601.10740v1 Announce Type: new Abstract: Modern neural networks rely on generic activation functions (ReLU, GELU, SiLU) that ignore the mathematical structure inherent in scientific data. We propose Neuro-Symbolic Activation Discovery, a framework that uses Genetic Programming to extract interpretable mathematical formulas from data and inject them as custom activation functions. Our key contribution is the discovery of a Geometric Transfer phenomenon: activation functions learned from particle physics data successfully generalize to ecological classification, outperforming standard activations (ReLU, GELU, […]

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