arXiv:2603.25747v1 Announce Type: new Abstract: The rapid evolution of Large Multimodal Models (LMMs) has enabled agents to perform complex digital and physical tasks, yet their deployment as autonomous decision-makers introduces substantial unintentional behavioral safety risks. However, the absence of a comprehensive safety benchmark remains a major bottleneck, as existing evaluations rely on low-fidelity environments, simulated APIs, or narrowly scoped tasks. To address this gap, we present BeSafe-Bench (BSB), a benchmark for exposing behavioral safety risks of situated agents […]

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Hey yall, I started working on this https://github.com/jimmie-jams/SilksongRL a while ago and finally managed to train an agent to beat one (1) boss. So, I figured it was time to share my glorious creation with the world. Jokes aside, I’d love to hear your thoughts! There are more environments/bosses already configured and it’s very easy to add new ones as well but I just don’t have the time/compute to train agents at a faster rate than I currently […]

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arXiv:2601.12282v1 Announce Type: new Abstract: The functions of different regions of the human brain are closely linked to their distinct cytoarchitecture, which is defined by the spatial arrangement and morphology of the cells. Identifying brain regions by their cytoarchitecture enables various scientific analyses of the brain. However, delineating these areas manually in brain histological sections is time-consuming and requires specialized knowledge. An automated approach is necessary to minimize the effort needed from human experts. To address this, we […]

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Point cloud completion is crucial for robotic tasks, especially with occluded and noisy industrial data. While two-dimensional image guidance has been traditional, pure point cloud methods increasingly achieve state-of-the-art results, making amodal completeness—recovering both visible and occluded parts—critical for robust interaction. Inspired by these insights, we propose MAG-Comp, a novel framework maximizing geometric information for amodal point cloud completion. MAG-Comp utilizes a Hierarchical Geometric Feature Encoder, a Class-Agnostic Geometric Memory Bank for shape priors, and a Dynamic Amodal […]

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Programmers use Null as different flags. It can hint at an absence, an undefined value, en error etc. Multiple semantics lead to coupling and defects. TL;DR: Null is schizophrenic and does not exist in real-world. Its creator regretted and programmers around the world suffer from it. Don’t be a part of it. Problems 😔 Coupling between callers and senders. If/Switch/Case Polluting. Null is not polymorphic with real objects. Hence, Null Pointer Exception Null does not exist on real-world. Thus, […]

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arXiv:2603.25835v1 Announce Type: new Abstract: Starlink has rapidly emerged as the world’s largest satellite constellation and the de facto reference system for low Earth orbit (LEO) networking research. Existing literature predominantly models Starlink as a static, symmetric, and fully deployed structure with uniformly distributed satellites. However, we reveal that Starlink’s actual deployment, orbital configurations, and operational dynamics fundamentally deviate from these idealized assumptions. Leveraging satellite observation data spanning 2019 to 2025, we demonstrate that the constellation is highly […]

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Advances in single-cell and spatial transcriptomic technologies have transformed tumor ecosystem profiling at cellular resolution. However, large scale studies on patient cohorts continue to rely on bulk transcriptomic data, where variation in tumor purity obscures tumor-intrinsic transcriptional signals and constrains downstream discovery. Many deconvolution methods report strong performance on synthetic bulk mixtures but fail to generalize to real patient cohorts because of unmodeled biological and technical variation. Here, we introduce TwinPurify, a representation learning framework that adapts the […]

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