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17,191 papers

#machine learning Preprint Open access Oct 2026

Sampling the XY model with an attention-based neural network

We present a transformer-based variational autoregressive network for sampling lattice systems with continuous degrees of freedom and apply it to the two-dimensional XY model near the Berezinskii-Kosterlitz-Thouless transition. The architecture is combined with physics-informed ingredients: locality-informed attention...

Piotr Bia{\l}as, Christian D. Morales, Tomasz Stebel et al. · 0 citations
#machine learning Preprint Oct 2026

Mesoscopic learning dynamics of extensive-width neural networks

Understanding how stochastic gradient descent learns internal representations in wide neural networks trained on rich target functions is a central problem in machine learning. We study this question in two-layer neural networks learning target functions represented by networks of the same architecture, with arbitrary...

Shu Zhou, Jean Barbier, Sebastian Goldt · 0 citations
#machine learning Preprint Open access Oct 2026

From Flow-Box Invariants to Global Conservation Laws: Machine Learning-Assisted Detection of Singularities and Near-Integrability

Conservation laws reveal invariant structure in dynamical systems and constrain their evolution to lower-dimensional level sets. Locally, however, per the flow-box theorem, every $d$-dimensional system generically admits $d-1$ functionally independent conservation laws near a regular point even though, generically, onl...

Jimmie Adriazola, Ioannis G. Kevrekidis, Panayotis G. Kevrekidis et al. · 0 citations
#machine learning Preprint Open access Oct 2026

Bridging the Language Gap in Scholarly Data II: Enhancing Gender Inference for Chinese Names

Perceived gender inference from names is important for inclusive scientometrics research, yet existing methods perform poorly on non-Western scholars. We address this gap for Chinese names, which appear in two forms, Hanzi and Pinyin, its Romanized form (e.g., Zhang Wei, Li Na). In international bibliographic records,...

Lisette Esp\'in-Noboa, Mingrong She, Ana Maria Jaramillo et al. · 0 citations
#machine learning Preprint Oct 2026

ECG-SDI: Single-lead Electrocardiogram Enables Continuous Sleep Depth Index Profiling and Scalable Digital Biomarkers for Sleep Health

Conventional sleep staging provides a coarse-grained representation that obscures within-stage depth variation. We developed ECG-SDI, a single-lead electrocardiography (ECG) framework for continuous sleep-depth profiling and digital biomarker extraction. Using 12,392 overnight polysomnographic recordings, we trained an...

Dong-Lin Xie, Qing-Shuo Zhao, Song-Chi Zhou et al. · 0 citations
#machine learning Preprint Oct 2026

Expressivity of IQP Feature-Map Quantum Kernels via Reproducing Kernel Hilbert Spaces

These results make the relationship between expressivity and data structure explicit for IQP kernels: expressive power translates into a practical benefit only when the accessible frequencies match with the structure of the data, which provides a criterion for selecting the bandwidth when the periodic or multimodal str...

Valeria Repetto, Stefano Melchionna, R. D'Aurizio · 0 citations
#machine learning Preprint Open access Oct 2026

HardEval: An Execution-Verified Benchmark for AI-Driven Security Hardening and Compliance Remediation

Implementing Security Technical Implementation Guide (STIG) controls remains a demanding operating-system administration task. Each natural-language security requirement must be translated into a precise and persistent configuration change. These changes span Secure Shell (SSH) configuration, authentication policy, aud...

Manohar Vellala, Soumya Banerjee, Sandip Roy et al. · 0 citations
#machine learning Preprint Open access Oct 2026

An Efficient Approach to Beetle Damage Detection of Banana Using Deep Learning

Visible surface damage of banana fruits by Basilepta subcostata (the banana fruit scarring beetle) can reduce their market value. Here, manual inspection of Banana fruits is subjective and difficult to scale. This study presents a lightweight framework based on YOLOv8n deep learning model for locating individual banana...

Md. Mehedi Hasan Naeem, Ishtiyak Ahmmad Araf, Md. Arefin Haque Mahir et al. · 0 citations
#machine learning Preprint Oct 2026

A Language-Informed Loss for Visual Generation

End-to-end visual generation with pixel-space loss has recently achieved competitive performance without the need for learned image tokenizers. In this work, we study whether language-informed supervision can provide a richer training signal than pixel loss for visual generation. We introduce LILIE (pronounced"lily"),...

Suchir Agarwal, Keshigeyan Chandrasegaran, Zi-Yu Chen et al. · 0 citations
#machine learning Preprint Open access Oct 2026

Scalable long-range machine learning interatomic potentials with electrical response for atomistic material modeling

Accurate atomistic simulations of materials under electric fields require long-range electrostatics and electrical-response modeling at length scales beyond the reach of conventional first-principles methods. Yet these capabilities remain difficult to reconcile with the scalability of machine-learning interatomic poten...

Yicheng Chen, Xiaoyun Yu, Hyejeong Song et al. · 0 citations
#machine learning Preprint Open access Oct 2026

Trajectory-Triggered Sparse Collaborative Decoding

Dense assistance methods such as speculative decoding repeatedly verify draft tokens with a target model, keeping target computation coupled to generation. We study sparse collaborative decoding, where a draft model generates most tokens and a target model is invoked only for short corrective segments. The key problem...

Amit Ranjan Trivedi, Sruthikesh Surineni, Kyong Ho Lee et al. · 0 citations
#machine learning Preprint Oct 2026

A general recipe for data-adaptive anytime-valid envelopes for iterative algorithms

It is shown how these boundaries can be directly coupled with a separate algorithmic analysis that derives the one-step recursion to provide a class of readymade anytime-valid envelopes across diverse settings including stochastic gradient descent (SGD), temporal difference learning, and Bures-Wasserstein SGD.

Soham Bonnerjee, Aaditya Ramdas · 0 citations

From tech blogs

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Microsoft Research Blog Nov 3, 2026

Learn the rules: The hacker mindset

Research Manager Mike Walker reflects on a career spanning hacker culture, cybersecurity, and AI, sharing lessons about trust, teamwork, leadership, and why solving difficult problems requires curiosity, judgment, agility—and an understanding of the rules. The post Learn the rules: The hacker mindset appeared first on Microsoft Research.

Google DeepMind Blog Nov 3, 2026

Agentic cheminformatics with Google Antigravity

Learn how Google Antigravity and our Cheminformatics Skills accelerate drug discovery workflows, search compounds, and propose novel rigidified macrocycles.

MIT News · Artificial Intelligence Oct 28, 2026

Making machines that can listen

Professor Paris Smaragdis develops computers with superhuman hearing for applications like speech recognition, music understanding, and environmental monitoring.

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