Nature Machine Intelligence

Article	Citations
Physical benchmarks for testing algorithms	842
A challenge for the law and artificial intelligence	717
Towards reproducible robotics research	548
Author Correction: A 5′ UTR language model for decoding untranslated regions of mRNA and function predictions	543
Author Correction: Integrated structure prediction of protein–protein docking with experimental restraints using ColabDock	493
Investigating machine moral judgement through the Delphi experiment	460
Physically constrained generative adversarial networks for improving precipitation fields from Earth system models	421
Wing-strain-based flight control of flapping-wing drones through reinforcement learning	380
A domain-adapted large language model to support clinicians in psychiatric clinical practice	380
From embodied intelligence to physical AI	373
A soft-packaged and portable rehabilitation glove capable of closed-loop fine motor skills	333
A statistical mechanics framework for Bayesian deep neural networks beyond the infinite-width limit	305
Tailored structured peptide design with a key-cutting machine approach	300
A multi-modal deep language model for contaminant removal from metagenome-assembled genomes	240
Identifying spatial single-cell-level interactions with graph transformer	219
Materiality and risk in the age of pervasive AI sensors	211
Discussions of machine versus living intelligence need more clarity	197
Artificial intelligence tackles the nature–nurture debate	196
Reusability report: Deep learning-based analysis of images and spectroscopy data with AtomAI	188
Quantum circuit optimization with AlphaTensor	182
Maximum diffusion reinforcement learning	178
Robust virtual staining of landmark organelles with Cytoland	176
Are neural network representations universal or idiosyncratic?	174
Large language models still struggle with false beliefs	166
Fast and generalizable micromagnetic simulation with deep neural nets	155

A Global South perspective for ethical algorithms and the State	148
Recurrent graph optimal transport for learning 3D flow motion in particle tracking	148
Bringing artificial intelligence to business management	145
Reshaping the discovery of self-assembling peptides with generative AI guided by hybrid deep learning	143
The curious case of the test set AUROC	143
Next-generation phenotyping of inherited retinal diseases from multimodal imaging with Eye2Gene	142
Generative AI for designing and validating easily synthesizable and structurally novel antibiotics	139
Zero-shot transfer of protein sequence likelihood models to thermostability prediction	138
Transformer-based protein generation with regularized latent space optimization	137
Direct conformational sampling from peptide energy landscapes through hypernetwork-conditioned diffusion	135
Deep neural networks with controlled variable selection for the identification of putative causal genetic variants	134
Pseudodata-based molecular structure generator to reveal unknown chemicals	134
Inferring spatial single-cell-level interactions through interpreting cell state and niche correlations learned by self-supervised graph transformer	131
Advancing ethics review practices in AI research	130
A question of trust for AI research in medicine	130
AI pioneers win 2024 Nobel prizes	129
Error-controlled non-additive interaction discovery in machine learning models	128
Integrated structure prediction of protein–protein docking with experimental restraints using ColabDock	128
What’s the next word in large language models?	127
How to break information cocoons	124
LLMs displaying less cognitive bias are not necessarily better decision makers	123
A new perspective on the simulation of stochastic problems in fluid mechanics with diffusion models	120
Machine learning prediction of enzyme optimum pH	116
Laplace neural operator for solving differential equations	116
Codon language embeddings provide strong signals for use in protein engineering	116
Learning from models beyond fine-tuning	115
Deep spectral component filtering as a foundation model for spectral analysis demonstrated in metabolic profiling	114
Multi-animal 3D social pose estimation, identification and behaviour embedding with a few-shot learning framework	111
Functional mimicry of Ruffini receptors with fibre Bragg gratings and deep neural networks enables a bio-inspired large-area tactile-sensitive skin	109
AI reality check	108
Life-threatening ventricular arrhythmia detection challenge in implantable cardioverter–defibrillators	107
Seeking a quantum advantage for machine learning	106
Collaborative creativity in AI	106
Bridging peptide presentation and T cell recognition with multi-task learning	106
What is in your LLM-based framework?	105
Accurate and robust protein sequence design with CarbonDesign	105
A personalized time-resolved 3D mesh generative model for unveiling normal heart dynamics	103
Morphological flexibility in robotic systems through physical polygon meshing	103
Foundation models in healthcare require rethinking reliability	100
The TRIPOD-P reporting guideline for improving the integrity and transparency of predictive analytics in healthcare through study protocols	99
Efficient generation of protein pockets with PocketGen	98
Deciphering RNA–ligand binding specificity with GerNA-Bind	98
Image-based generation for molecule design with SketchMol	97
Human–AI adaptive dynamics drives the emergence of information cocoons	95
A multi-modal pre-training transformer for universal transfer learning in metal–organic frameworks	91
Neural scaling of deep chemical models	91
Unsupervised learning of topological non-Abelian braiding in non-Hermitian bands	91
Autonomous environment-adaptive microrobot swarm navigation enabled by deep learning-based real-time distribution planning	89
Multimodal learning with graphs	87
Unifying multi-sample network inference from prior knowledge and omics data with CORNETO	86

Uncertainty-guided dual-views for semi-supervised volumetric medical image segmentation	86
Learning high-level visual representations from a child’s perspective without strong inductive biases	85
Algorithmic fairness and bias mitigation for clinical machine learning with deep reinforcement learning	85
Deep learning supported discovery of biomarkers for clinical prognosis of liver cancer	84
LLM-based agentic systems in medicine and healthcare	84
Tandem mass spectrum prediction for small molecules using graph transformers	84
Advanced AI assistants that act on our behalf may not be ethically or legally feasible	83
ARNLE model identifies prevalence potential of SARS-CoV-2 variants	82
Towards generalizable and interpretable three-dimensional tracking with inverse neural rendering	82
Improving de novo molecular design with curriculum learning	82
Enhancing deep learning-based field reconstruction with a differentiable learning framework	81
ResGen is a pocket-aware 3D molecular generation model based on parallel multiscale modelling	81
Reconstructing growth and dynamic trajectories from single-cell transcriptomics data	80
Anniversary AI reflections	80
Human-behaviour-based social locomotion model improves the humanization of social robots	80
Learning plastic matching of robot dynamics in closed-loop central pattern generators	80
A neuro-vector-symbolic architecture for solving Raven’s progressive matrices	79
Moving towards genome-wide data integration for patient stratification with Integrate Any Omics	78
A method for multiple-sequence-alignment-free protein structure prediction using a protein language model	77
Reusability report: Exploring the transferability of self-supervised learning models from single-cell to spatial transcriptomics	77
Foundation models and the privatization of public knowledge	76
Differentiable visual computing for inverse problems and machine learning	75
Synthetic data accelerates the development of generalizable learning-based algorithms for X-ray image analysis	75
Geometric deep learning reveals the spatiotemporal features of microscopic motion	75
Writing the rules in AI-assisted writing	74
Model-based reinforcement learning for ultrasound-driven autonomous microrobots	73
A multimodal cell-free RNA language model for liquid biopsy applications	73
From attribution maps to human-understandable explanations through Concept Relevance Propagation	72
A social network for AI	71
Distinguishing two features of accountability for AI technologies	70
Learning intermediate physical states for inverse metasurface design	69
Successful implementation of the EU AI Act requires interdisciplinary efforts	68
Publisher Correction: A neural machine code and programming framework for the reservoir computer	68
An interaction-derived graph learning framework for scoring protein–peptide complexes	68
Mask-prior-guided denoising diffusion improves inverse protein folding	67
Delineating the effective use of self-supervised learning in single-cell genomics	67
Learning integral operators via neural integral equations	67
Closed-form continuous-time neural networks	66
Mode switching in organisms for solving explore-versus-exploit problems	66
Benchmarking AI-powered docking methods from the perspective of virtual screening	66
Lessons from a challenge on forecasting epileptic seizures from non-cerebral signals	66
Active learning for optimal intervention design in causal models	65
Leveraging language model for advanced multiproperty molecular optimization via prompt engineering	65
Sampling-enabled scalable manifold learning unveils the discriminative cluster structure of high-dimensional data	64
Defending ChatGPT against jailbreak attack via self-reminders	64
CHGNet as a pretrained universal neural network potential for charge-informed atomistic modelling	64
Advances, challenges and opportunities in creating data for trustworthy AI	63
Artificial intelligence-powered electronic skin	63
On board with COMET to improve omics prediction models	62
Interpretable meta-score for model performance	62
Current-diffusion model for metasurface structure discoveries with spatial-frequency dynamics	61
Invalid SMILES are beneficial rather than detrimental to chemical language models	61
A new eye on inherited retinal disease	61
Listening in to perceived speech with contrastive learning	61
Large language models challenge the future of higher education	61
A unified deep framework for peptide–major histocompatibility complex–T cell receptor binding prediction	61
Machine learning-enabled globally guaranteed evolutionary computation	60
Teaching machines to blend electrolyte cocktails	59
The incentive gap in data work in the era of large models	59
A computational framework for neural network-based variational Monte Carlo with Forward Laplacian	59
Solving sparse finite element problems on neuromorphic hardware	59
Mitigating the missing-fragmentation problem in de novo peptide sequencing with a two-stage graph-based deep learning model	58
A generalizable deep learning framework for inferring fine-scale germline mutation rate maps	56
Lossless data compression by large models	55
Data-driven discovery of movement-linked heterogeneity in neurodegenerative diseases	55
Fast, scale-adaptive and uncertainty-aware downscaling of Earth system model fields with generative machine learning	55
Deep transfer operator learning for partial differential equations under conditional shift	54
Versatile cardiovascular signal generation with a unified diffusion transformer	54
Unsupervised ensemble-based phenotyping enhances discoverability of genes related to left-ventricular morphology	54
Predicting the conformational flexibility of antibody and T cell receptor complementarity-determining regions	54
Deep learning for predicting rate-induced tipping	54
Three types of incremental learning	52
Augmenting large language models with chemistry tools	52
Incorporating physics into data-driven computer vision	52
Automated construction of cognitive maps with visual predictive coding	51
The importance of negative training data for robust antibody binding prediction	51
AI podcasts for the summer	51
Competing Biases underlie Overconfidence and Underconfidence in LLMs	51
Deconstructing the generalization gap	50
Discovering neural policies to drive behaviour by integrating deep reinforcement learning agents with biological neural networks	50

A family of large language models for materials research with insights into model adaptability in continued pretraining	50
Generalized biological foundation model with unified nucleic acid and protein language	50
Pan-Peptide Meta Learning for T-cell receptor–antigen binding recognition	50
A process-centric manipulation taxonomy for the organization, classification and synthesis of tactile robot skills	49
Predicting the prevalence of complex genetic diseases from individual genotype profiles using capsule networks	49
When large language models are reliable for judging empathic communication	48
Deep learning-based prediction of the selection factors for quantifying selection in immune receptor repertoires	48
Publisher Correction: Advancing ethics review practices in AI research	48
Multiscale topology-enabled structure-to-sequence transformer for protein–ligand interaction predictions	47
Synergy-based robotic quadruped leveraging passivity for natural intelligence and behavioural diversity	47
Aligning generalization between humans and machines	46
Space missions out of this world with AI	46
Labelling instructions matter in biomedical image analysis	46
Realistic morphology-preserving generative modelling of the brain	46
Visual speech recognition for multiple languages in the wild	45
Design of prime-editing guide RNAs with deep transfer learning	45
Reply to: Inability of a graph neural network heuristic to outperform greedy algorithms in solving combinatorial optimization problems	44
No chemical killer AI (yet)	43
A soft touch for robots	43
A framework for tool cognition in robots without prior tool learning or observation	42
An integrated framework to accelerate protein design through mutagenesis	42
Geometric deep learning of particle motion by MAGIK	42
Why design choices matter in recommender systems	41
Author Correction: Predicting equilibrium distributions for molecular systems with deep learning	41
Towards unveiling sensitive and decisive patterns in explainable AI with a case study in geometric deep learning	41
Accelerating protein engineering with fitness landscape modelling and reinforcement learning	40
Towards a universal model for spin–orbit physics	40
A disease-specific language model for variant pathogenicity in cardiac and regulatory genomics	40
On the caveats of AI autophagy	40
Embodied large language models enable robots to complete complex tasks in unpredictable environments	40
Weak signal extraction enabled by deep neural network denoising of diffraction data	40
Type II mechanoreceptors and cuneate spiking neuronal network enable touch localization on a large-area e-skin	40