arXiv:2509.17636v2 Announce Type: replace Abstract: Whitening is a classical technique in unsupervised learning that can facilitate estimation tasks by standardizing data. An important application is the estimation of latent variable models via the decomposition of tensors built from high-order moments. In particular, whitening orthogonalizes the means of a spherical Gaussian mixture model (GMM), thereby making the corresponding moment tensor orthogonally decomposable, hence easier to decompose. However, in the large-dimensional regime (LDR) where data are high-dimensional and scarce, the […]

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arXiv:2411.06501v3 Announce Type: replace-cross Abstract: We study the regret in stochastic Multi-Armed Bandits (MAB) with multiple agents that communicate over an arbitrary connected communication graph. We analyzed a variant of Cooperative Successive Elimination algorithm, COOP-SE, and show an individual regret bound of $O(R/ m + A^2 + A sqrt{log T})$ and a nearly matching lower bound. Here $A$ is the number of actions, $T$ the time horizon, $m$ the number of agents, and $R = sum_{Delta_i > 0}log(T)/Delta_i$ […]

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arXiv:2602.10250v1 Announce Type: new Abstract: As 3GPP systems have strengthened security at the upper layers of the cellular stack, plaintext PHY and MAC layers have remained relatively understudied, though interest in them is growing. In this work, we explore lower-layer exploitation in modern 5G, where recent releases have increased the number of lower-layer control messages and procedures, creating new opportunities for practical attacks. We present two practical attacks and evaluate them in a controlled lab testbed. First, we […]

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arXiv:2601.07978v1 Announce Type: new Abstract: Distributed multi-agent systems use large language models to enable collaborative intelligence while preserving privacy, yet systematic evaluations of long-term memory under network constraints remain limited. This study presents a flexible testbed comparing mem0, a vector-based memory framework, and Graphiti, a graph-based knowledge graph, using the LOCOMO long-context benchmark. Experiments were conducted under unconstrained and constrained network conditions, measuring computational, financial, and accuracy metrics. Results indicate that mem0 significantly outperforms Graphiti in efficiency, with […]

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arXiv:2601.04327v1 Announce Type: new Abstract: Parallel programming is central to HPC and AI, but producing code that is correct and fast remains challenging, especially for OpenMP GPU offload, where data movement and tuning dominate. Autonomous coding agents can compile, test, and profile on target hardware, but outputs are brittle without domain scaffolding. We present ParaCodex, an HPC-engineer workflow that turns a Codex-based agent into an autonomous OpenMP GPU offload system using staged hotspot analysis, explicit data planning, correctness […]

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Published on December 4, 2025 6:46 PM GMT Highly capable AI systems might end up deciding the future. Understanding what will drive those decisions is therefore one of the most important questions we can ask. Many people have proposed different answers. Some predict that powerful AIs will learn to intrinsically pursue reward. Others respond by saying reward is not the optimization target, and instead reward “chisels” a combination of context-dependent cognitive patterns into the AI. Some argue that […]

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Active inference (AIF) unifies exploration and exploitation by minimizing the Expected Free Energy (EFE), balancing epistemic value (information gain) and pragmatic value (task performance) through a curiosity coefficient. Yet it has been unclear when this balance yields both coherent learning and efficient decision-making: insufficient curiosity can drive myopic exploitation and prevent uncertainty resolution, while excessive curiosity can induce unnecessary exploration and regret. We establish the first theoretical guarantee for EFE-minimizing agents, showing that a single requirement–sufficient curiosity–simultaneously ensures […]

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There’s plenty of hype around AI and robots in healthcare, but the problem that’s actually costing hospitals money right now is operating room coordination. Two to four hours of OR time is lost every single day, not because of the surgeries themselves, but because of everything in between from manual scheduling and coordination chaos to guesswork about room […]

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arXiv:2601.09822v1 Announce Type: new Abstract: Despite recent advancements in Large Language Models (LLMs), complex Software Engineering (SE) tasks require more collaborative and specialized approaches. This concept paper systematically reviews the emerging paradigm of LLM-based multi-agent systems, examining their applications across the Software Development Life Cycle (SDLC), from requirements engineering and code generation to static code checking, testing, and debugging. We delve into a wide range of topics such as language model selection, SE evaluation benchmarks, state-of-the-art agentic frameworks […]

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