arXiv:2601.01010v2 Announce Type: replace-cross Abstract: We provide an overview of high dimensional dynamical systems driven by random matrices, focusing on applications to simple models of learning and generalization in machine learning theory. Using both cavity method arguments and path integrals, we review how the behavior of a coupled infinite dimensional system can be characterized as a stochastic process for each single site of the system. We provide a pedagogical treatment of dynamical mean field theory (DMFT), a framework […]

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arXiv:2604.08565v1 Announce Type: new Abstract: At typical context lengths, the feed-forward MLP block accounts for a large share of a transformer’s compute budget, motivating sparse alternatives to dense MLP blocks. We study sparse, tree-structured feed-forward layers as drop-in replacements for MLP blocks in deep transformer architectures, enabling conditional computation via hard hierarchical routing without a separate router network. We demonstrate for the first time that this form of tree-structured conditional sparsity can be applied for autoregressive language modeling […]

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arXiv:2602.06081v1 Announce Type: new Abstract: Large Language Models (LLMs) often exhibit pronounced context-dependent variability that undermines predictable multi-agent behavior in tasks requiring strategic thinking. Focusing on models that range from 7 to 9 billion parameters in size engaged in a ten-round repeated Prisoner’s Dilemma, we evaluate whether short, costless pre-play messages emulating the cheap-talk paradigm affect strategic stability. Our analysis uses simulation-level bootstrap resampling and nonparametric inference to compare cooperation trajectories fitted with LOWESS regression across both the […]

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arXiv:2603.25509v1 Announce Type: cross Abstract: We propose a method for constructing distribution-free prediction intervals in nonparametric instrumental variable regression (NPIV), with finite-sample coverage guarantees. Building on the conditional guarantee framework in conformal inference, we reformulate conditional coverage as marginal coverage over a class of IV shifts $mathcal{F}$. Our method can be combined with any NPIV estimator, including sieve 2SLS and other machine-learning-based NPIV methods such as neural networks minimax approaches. Our theoretical analysis establishes distribution-free, finite-sample coverage over […]

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A new free course from Binance Academy and Marlin Foundation teaches Web3 developers how to use Trusted Execution Environments (TEEs) to build fast, private, and verifiable decentralized apps. The program covers offchain computing, confidential AI, DeFi use cases, and hands-on deployment, making enterprise-grade secure hardware accessible to anyone building in Web3.

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arXiv:2601.22255v1 Announce Type: new Abstract: This article sets off for an exploration of the still evolving discourse surrounding artificial intelligence (AI) in the wake of the release of ChatGPT. It scrutinizes the pervasive narratives that are shaping the societal engagement with AI, spotlighting key themes such as agency and decision-making, autonomy, truthfulness, knowledge processing, prediction, general purpose, neutrality and objectivity, apolitical optimization, sustainability game-changer, democratization, mass unemployment, and the dualistic portrayal of AI as either a harbinger of […]

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arXiv:2604.04977v1 Announce Type: new Abstract: Software supply chain security compromises often stem from cascaded interactions of vulnerabilities, for example, between multiple vulnerable components. Yet, Software Bill of Materials (SBOM)-based pipelines for security analysis typically treat scanner findings as independent per-CVE (Common Vulnerabilities and Exposures) records. We propose a new research direction based on learning multi-vulnerability attack chains through a novel SBOM-driven graph-learning approach. This treats SBOM structure and scanner outputs as a dependency-constrained evidence graph rather than a […]

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How are you, hacker? 🪐 What’s happening in tech today, April 18, 2026? The HackerNoon Newsletter brings the HackerNoon homepage straight to your inbox. On this day, Osborne Computer introduced in 1983, and we present you with these top quality stories. From What Ghost Murmur Technology Actually Is (Its Not a Heartbeat Detector) to The Proof of Usefulness Algorithm: Is It Good? Do People Use It?, let’s dive right in. What Ghost Murmur Technology Actually Is (Its Not […]

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