arXiv:2601.07880v1 Announce Type: new Abstract: Identity Security Posture Management (ISPM) is a core challenge for modern enterprises operating across cloud and SaaS environments. Answering basic ISPM visibility questions, such as understanding identity inventory and configuration hygiene, requires interpreting complex identity data, motivating growing interest in agentic AI systems. Despite this interest, there is currently no standardized way to evaluate how well such systems perform ISPM visibility tasks on real enterprise data. We introduce the Sola Visibility ISPM Benchmark, […]

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Intelligent medical image analysis is essential for clinical decision support but is often limited by scarce annotations, constrained computational resources, and suboptimal model generalization. To address these challenges, we propose a lightweight medical image classification framework that integrates self-supervised contrastive learning with quantum-enhanced feature modeling. MobileNetV2 is employed as a compact backbone and pretrained using a SimCLR-style self-supervised paradigm on unlabeled images. A lightweight parameterized quantum circuit (PQC) is embedded as a quantum feature enhancement module, forming a […]

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In this month’s episode of Functional Futures, our guest is Edward Kmett – Head of Software Engineering at Groq and the author of many widely-used Haskell libraries. In the episode, we dive into his life story – how he went from being broke and in debt to learning category theory and authoring numerous Haskell libraries. We also talk about programming languages and projects beyond Haskell that make Edward excited right now. We hope you’ll enjoy the episode. As […]

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arXiv:2601.01127v2 Announce Type: replace-cross Abstract: This paper, introducing a novel method in philomatics, draws on Wittgenstein’s concept of family resemblance from analytic philosophy to develop a clustering algorithm for machine learning. According to Wittgenstein’s Philosophical Investigations (1953), family resemblance holds that members of a concept or category are connected by overlapping similarities rather than a single defining property. Consequently, a family of entities forms a chain of items sharing overlapping traits. This philosophical idea naturally lends itself to […]

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arXiv:2602.21278v1 Announce Type: new Abstract: As memory increasingly dominates system cost and energy, heterogeneous on-chip memory systems that combine technologies with complementary characteristics are becoming essential. Gain Cell RAM (GCRAM) offers higher density, lower power, and tunable retention, expanding the design space beyond conventional SRAM. To this end, we create an OpenGCRAM compiler supporting both SRAM and GCRAM. It generates macro-level designs and layouts for commercial CMOS processes and characterizes area, delay, and power across user-defined configurations. The […]

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arXiv:2511.19566v2 Announce Type: replace-cross Abstract: Open weight models, which are ubiquitous, rarely provide access to their training data or loss function. This makes modifying such models for tasks such as pruning or unlearning, which are constrained by this unavailability, an active area of research. Existing techniques typically require gradients or ground-truth labels, rendering them infeasible in settings with limited computational resources. In this work, we investigate the fundamental question of identifying components that are critical to the model’s […]

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arXiv:2602.23457v1 Announce Type: new Abstract: Soft robots enable safe, adaptive interaction with complex environments but remain difficult to sense and control due to their highly deformable structures. Architected soft materials such as helicoid lattices offer tunable stiffness and strength but are challenging to instrument because of their sparse geometry. We introduce a fabrication method for embedding air channels into helicoid-based soft continuum robots. Multi-material segments fabricated via vision-controlled jetting in a single print interface with PCBs housing miniature […]

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arXiv:2602.03466v4 Announce Type: replace-cross Abstract: Large language models (LLMs) can generate structured artifacts, but using them as dependable optimizers for scientific design requires a mechanism for iterative improvement under black-box evaluation. Here, we cast quantum circuit synthesis as a closed-loop, test-time optimization problem: an LLM proposes edits to a fixed-length gate list, and an external simulator evaluates the resulting state with the Meyer-Wallach (MW) global entanglement measure. We introduce a lightweight test-time learning recipe that can reuse prior […]

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Raga identification in Indian Art Music (IAM) remains challenging due to the presence of numerous rarely performed Ragas that are not represented in available training datasets. Traditional classification models struggle in this setting, as they assume a closed set of known categories and therefore fail to recognise or meaningfully group previously unseen Ragas. Recent works have tried categorizing unseen Ragas, but they run into a problem of catastrophic forgetting, where the knowledge of previously seen Ragas is diminished. […]

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