OOIR: Observatory of International Research

Papers

(The H4-Index of Nature Machine Intelligence is 88. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2022-08-01 to 2026-08-01.)

Article	Citations
Physical benchmarks for testing algorithms	961
A challenge for the law and artificial intelligence	845
Towards reproducible robotics research	626
Author Correction: Integrated structure prediction of protein–protein docking with experimental restraints using ColabDock	622
Artificial intelligence tackles the nature–nurture debate	610
Tailored structured peptide design with a key-cutting machine approach	504
Identifying spatial single-cell-level interactions with graph transformer	490
A multi-modal deep language model for contaminant removal from metagenome-assembled genomes	430
From embodied intelligence to physical AI	427
A domain-adapted large language model to support clinicians in psychiatric clinical practice	399
Discussions of machine versus living intelligence need more clarity	368
A soft-packaged and portable rehabilitation glove capable of closed-loop fine motor skills	351
Author Correction: A 5′ UTR language model for decoding untranslated regions of mRNA and function predictions	339
Neural sampling from cognitive maps enables goal-directed imagination and planning	261
Wing-strain-based flight control of flapping-wing drones through reinforcement learning	243
A statistical mechanics framework for Bayesian deep neural networks beyond the infinite-width limit	227
Physically constrained generative adversarial networks for improving precipitation fields from Earth system models	217
Investigating machine moral judgement through the Delphi experiment	213
Materiality and risk in the age of pervasive AI sensors	205
A question of trust for AI research in medicine	199
Deep neural networks with controlled variable selection for the identification of putative causal genetic variants	192
AI pioneers win 2024 Nobel prizes	184
Large language models still struggle with false beliefs	182
Reusability report: Deep learning-based analysis of images and spectroscopy data with AtomAI	180
Advancing ethics review practices in AI research	172

Robust virtual staining of landmark organelles with Cytoland	165
Inferring spatial single-cell-level interactions through interpreting cell state and niche correlations learned by self-supervised graph transformer	163
Fast and generalizable micromagnetic simulation with deep neural nets	162
A Global South perspective for ethical algorithms and the State	158
Transformer-based protein generation with regularized latent space optimization	155
Are neural network representations universal or idiosyncratic?	154
Pseudodata-based molecular structure generator to reveal unknown chemicals	154
Maximum diffusion reinforcement learning	154
Zero-shot transfer of protein sequence likelihood models to thermostability prediction	153
The curious case of the test set AUROC	152
Reshaping the discovery of self-assembling peptides with generative AI guided by hybrid deep learning	151
Recurrent graph optimal transport for learning 3D flow motion in particle tracking	151
Direct conformational sampling from peptide energy landscapes through hypernetwork-conditioned diffusion	149
Quantum circuit optimization with AlphaTensor	147
Next-generation phenotyping of inherited retinal diseases from multimodal imaging with Eye2Gene	145
Generative AI for designing and validating easily synthesizable and structurally novel antibiotics	143
How to break information cocoons	142
What’s the next word in large language models?	142
LLMs displaying less cognitive bias are not necessarily better decision makers	140
A new perspective on the simulation of stochastic problems in fluid mechanics with diffusion models	140
Deep spectral component filtering as a foundation model for spectral analysis demonstrated in metabolic profiling	137
Codon language embeddings provide strong signals for use in protein engineering	137
Learning from models beyond fine-tuning	137
Integrated structure prediction of protein–protein docking with experimental restraints using ColabDock	132
Multi-animal 3D social pose estimation, identification and behaviour embedding with a few-shot learning framework	132
Empowering biomedical evidence exploration and synthesis with deep knowledge graph research	131
Guiding generative models to uncover diverse and novel crystals via reinforcement learning	129
Laplace neural operator for solving differential equations	129
Error-controlled non-additive interaction discovery in machine learning models	128
Machine learning prediction of enzyme optimum pH	120
AI reality check	118
The TRIPOD-P reporting guideline for improving the integrity and transparency of predictive analytics in healthcare through study protocols	117
What is in your LLM-based framework?	115
Collaborative creativity in AI	114
Seeking a quantum advantage for machine learning	114
Bridging peptide presentation and T cell recognition with multi-task learning	114
Accurate and robust protein sequence design with CarbonDesign	110
Foundation models in healthcare require rethinking reliability	110
A personalized time-resolved 3D mesh generative model for unveiling normal heart dynamics	109
Deciphering RNA–ligand binding specificity with GerNA-Bind	107
Deep learning supported discovery of biomarkers for clinical prognosis of liver cancer	103
Image-based generation for molecule design with SketchMol	102
Tandem mass spectrum prediction for small molecules using graph transformers	100
Unifying multi-sample network inference from prior knowledge and omics data with CORNETO	99
Unsupervised learning of topological non-Abelian braiding in non-Hermitian bands	98
Life-threatening ventricular arrhythmia detection challenge in implantable cardioverter–defibrillators	98
Uncertainty-guided dual-views for semi-supervised volumetric medical image segmentation	96
A multi-modal pre-training transformer for universal transfer learning in metal–organic frameworks	96
Learning high-level visual representations from a child’s perspective without strong inductive biases	96
LLM-based agentic systems in medicine and healthcare	95

Human–AI adaptive dynamics drives the emergence of information cocoons	94
Morphological flexibility in robotic systems through physical polygon meshing	94
Neural scaling of deep chemical models	94
Multimodal learning with graphs	93
Advanced AI assistants that act on our behalf may not be ethically or legally feasible	92
Algorithmic fairness and bias mitigation for clinical machine learning with deep reinforcement learning	92
Efficient generation of protein pockets with PocketGen	92
Foundation models and the privatization of public knowledge	91
Towards generalizable and interpretable three-dimensional tracking with inverse neural rendering	91
Reusability report: Exploring the transferability of self-supervised learning models from single-cell to spatial transcriptomics	91
Anniversary AI reflections	89
Writing the rules in AI-assisted writing	89
ARNLE model identifies prevalence potential of SARS-CoV-2 variants	88