Nature Machine Intelligence, Published online: 24 August 2026; doi:10.1038/s42256-026-01290-0
Implicit neural representations can turn massive scientific measurements into compact functions. A hierarchical approach now helps these representations preserve richer fine-scale detail.Nature Machine Intelligence, Published online: 24 August 2026; doi:10.1038/s42256-026-01287-9
Ni et al. present WIEN-INR, an implicit neural representation for scientific data compression. It operates in the multiscale wavelet domain to improve compression as well as preserve fine details and signal fidelity.Nature Machine Intelligence, Published online: 24 August 2026; doi:10.1038/s42256-026-01297-7
Shepherd et al. propose end-to-end AI control of lower-limb exoskeletons based on real-time estimates of physiological signals.Nature Machine Intelligence, Published online: 19 August 2026; doi:10.1038/s42256-026-01291-z
Chen, Wang, Li et al. introduce VITAL, a dual-channel deep learning framework that co-learns sequence and structural contexts to quantitatively predict peptide–protein interactions, map binding interfaces and estimate affinity.Nature Machine Intelligence, Published online: 18 August 2026; doi:10.1038/s42256-026-01301-0
Frontier large language models (LLMs) have rapidly developed from helpful coding assistants to highly capable cybersecurity systems. After several security incidents in the past few months, more oversight and a strong focus on safe testing and deployment seem needed.Nature Machine Intelligence, Published online: 18 August 2026; doi:10.1038/s42256-026-01285-x
Pan et al. present CoxRTL, a recalibrated transfer learning strategy that leverages external cohorts to improve survival prediction under covariate shift when target training data are limited and deployment outcomes are unavailable.Nature Machine Intelligence, Published online: 17 August 2026; doi:10.1038/s42256-026-01279-9
Cheston et al. develop a machine learning pipeline that identifies 20 iconic jazz pianists from audio recordings with up to 94% accuracy, revealing how melody, harmony, rhythm and dynamics shape each performer’s individual musical fingerprint.Nature Machine Intelligence, Published online: 14 August 2026; doi:10.1038/s42256-026-01276-y
Chen et al. explore limitations of current knowledge editing techniques in large language models and propose three promising research directions that respect the complexity of knowledge representation in a real-world setting.Nature Machine Intelligence, Published online: 14 August 2026; doi:10.1038/s42256-026-01281-1
Wang et al. summarize advances in machine listening and speaking, speech-based interaction, and audio–visual understanding.Nature Machine Intelligence, Published online: 12 August 2026; doi:10.1038/s41598-026-62801-y
Model-free multiparametric analysis of SHG images reveals collagen signatures in breast cancerNature Machine Intelligence, Published online: 12 August 2026; doi:10.1038/s41598-026-66901-7
Development of samarium-153 oxide loaded polystyrene radiotracer particles for gamma scintigraphy of whole gastrointestinal transit studyNature Machine Intelligence, Published online: 12 August 2026; doi:10.1038/s41598-026-64954-2
AlzheiNN: a convolutional neural network-based model for Alzheimer’s disease classificationNature Machine Intelligence, Published online: 12 August 2026; doi:10.1057/s41599-026-08691-x
Service trade liberalization and manufacturing value chain upgrading: a quasi-natural experiment from ChinaNature Machine Intelligence, Published online: 12 August 2026; doi:10.1057/s41599-026-08677-9
The impact of CEOs’ multidisciplinary backgrounds on corporate financing and investment maturity mismatchNature Machine Intelligence, Published online: 12 August 2026; doi:10.1038/s41598-026-66659-y
Experiences of kinesiophobia in patients with chronic obstructive pulmonary disease: a qualitative phenomenological studyNature Machine Intelligence, Published online: 12 August 2026; doi:10.1038/s41598-026-66068-1
Multi-level violence recognition via hybrid convolutional-attention and recurrent architecturesNature Machine Intelligence, Published online: 12 August 2026; doi:10.1038/s41598-026-63846-9
Correction: A five-dimensional classical framework for gravitational and quantum phenomenaNature Machine Intelligence, Published online: 12 August 2026; doi:10.1038/s42256-026-01292-y
Wang et al. design efficient robot–environment interaction representations that achieve generalization across articulated robotic hand models and task adaptability in diverse cluttered grasping scenarios, suggesting a path towards general-purpose robotics.Nature Machine Intelligence, Published online: 10 August 2026; doi:10.1038/s42256-026-01280-2
Johnson et al. demonstrate an autonomous three-bar tensegrity robot capable of robust locomotion across varied terrains even after extreme impacts, including a 5.7-m drop onto asphalt.Nature Machine Intelligence, Published online: 05 August 2026; doi:10.1038/s42256-026-01275-z
A new deep learning method enables molecular dynamics simulations over longer time scales while still achieving accurate physical property prediction.
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