---
title: "Nature Machine Intelligence: 17 papers, last 30 days"
description: "Nature Machine Intelligence published 17 papers in the last 30 days (2026-09-27 to 2026-10-26), ranking #44 of 239 journals."
url: https://scholar4ai.com/journals/nature-machine-intelligence
markdown_url: https://scholar4ai.com/journals/nature-machine-intelligence.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "Nature Machine Intelligence published 17 papers in the last 30 days (2026-09-27 to 2026-10-26), ranking #44 of 239 journals."
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-10-26T14:32:25+09:00
window: 2026-09-27 to 2026-10-26
source: OpenAlex (CC0)
---

# Nature Machine Intelligence

- 5 papers in the last 7 days
- category: AI
- publisher: Nature Portfolio
- ISSN 2522-5839

Back to the ranking: https://scholar4ai.com/rankings/journals.md

## Key findings

- Nature Machine Intelligence published 17 papers in the last 30 days (2026-09-27 to 2026-10-26), ranking #44 of 239 journals.
- Leading institutions: Centre National de la Recherche Scientifique (2), Chinese Academy of Sciences (2) and Zhejiang University (2).
- Countries: China (6), United Kingdom (4) and United States (4).
- From Oct 2023 to Sep 2026, Nature Machine Intelligence published 585 papers (16 a month on average, by publication date in OpenAlex).
- Its most frequent keywords over that period were “large language models” (75), “graph neural networks” (27) and “deep learning” (25).
- Its most-cited paper of the period is “A framework to evaluate machine learning crystal stability predictions” (2025-06-23), with 159 citations.

## The last 36 months

*Papers by publication date, Oct 2023 to Sep 2026*

| Oct 23–Sep 24 | Oct 24–Sep 25 | Oct 25–Sep 26 | 36 months |
|---:|---:|---:|---:|
| 183 | 209 | 193 | 585 |

*Most frequent keywords, Oct 2023 to Sep 2026*

| # | Keyword | Papers |
|---:|---|---:|
| 1 | [large language models](https://scholar4ai.com/keywords/large-language-models.md) | 75 |
| 2 | [graph neural networks](https://scholar4ai.com/keywords/graph-neural-networks.md) | 27 |
| 3 | deep learning | 25 |
| 4 | drug discovery | 22 |
| 5 | generative AI | 21 |
| 6 | foundation models | 19 |
| 7 | reinforcement learning | 18 |
| 8 | self-supervised learning | 16 |
| 9 | transformer models | 16 |
| 10 | transfer learning | 14 |

*Most-cited papers published Oct 2023 to Sep 2026*

| # | Citations | Per month | Title | Journal | Published | Authors |
|---:|---:|---:|---|---|---|---|
| 1 | 159 | 9.9 | [A framework to evaluate machine learning crystal stability predictions](https://doi.org/10.1038/s42256-025-01055-1) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | 2025-06-23 | Janosh Riebesell, Rhys E. A. Goodall, Philipp Benner et al. |
| 2 | 130 | 6.7 | [Embodied large language models enable robots to complete complex tasks in unpredictable environments](https://doi.org/10.1038/s42256-025-01005-x) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | 2025-03-18 | Ruaridh Mon-Williams, Gen Li, Ran Long et al. |
| 3 | 100 | 6.8 | [A semantic-enhanced multi-modal remote sensing foundation model for Earth observation](https://doi.org/10.1038/s42256-025-01078-8) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | 2025-08-04 | Kang Wu, Yingying Zhang, Yingying Zhang et al. |
| 4 | 98 | 6.8 | [Kolmogorov–Arnold graph neural networks for molecular property prediction](https://doi.org/10.1038/s42256-025-01087-7) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | 2025-08-11 | Longlong Li, Yipeng Zhang, Guanghui Wang et al. |
| 5 | 96 | 5.1 | [A predictive machine learning force-field framework for liquid electrolyte development](https://doi.org/10.1038/s42256-025-01009-7) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | 2025-04-01 | Sheng Gong, Yumin Zhang, Zhenliang Mu et al. |

*Papers, newest first.*

| Date | Title | Journal | Authors | Affiliations |
|---|---|---|---|---|
| 2026-10-23 | [Efficient equivariant framework for universal charge density prediction](https://doi.org/10.1038/s42256-026-01326-5) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | Xiwen Li, Zaizhou Xin, Hongyu Yu et al. | Fudan University; State Key Laboratory of Surface Physics |
| 2026-10-23 | [Guidelines for evaluating structure-based methods for protein–ligand binding prediction](https://doi.org/10.1038/s42256-026-01331-8) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | Viet-Khoa Tran-Nguyen, Pedro Ballester | Délégation Paris 5; Centre National de la Recherche Scientifique; Inserm; … |
| 2026-10-20 | [Physics-informed machine learning: a hybrid lens for fluid dynamics](https://doi.org/10.1038/s42256-026-01319-4) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | Kai Fukami, Romit Maulik | Tohoku University; Purdue University West Lafayette |
| 2026-10-20 | [Agentic inequality](https://doi.org/10.1038/s42256-026-01318-5) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | Matthew Sharp, Omer Bilgin, Iason Gabriel et al. | University of Oxford; Google DeepMind (United Kingdom) |
| 2026-10-20 | [Lagrangian–Eulerian learning of flow field and trajectories with TrajectoryFlowNet](https://doi.org/10.1038/s42256-026-01316-7) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | Jiang Wan, Hongping Wang, Bo Liu et al. | Chinese Academy of Sciences; University of Chinese Academy of Sciences; Institute of Mechanics; … |
| 2026-10-19 | [Reusability report: multi-sample omics network inference operates in distinct robustness regimes defined by prior knowledge and data availability](https://doi.org/10.1038/s42256-026-01311-y) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | Xabier Martinez‐de‐Morentin, Sameer Ahmad Khan, Itziar Cenzano et al. | King Abdullah University of Science and Technology; Ilia State University; Karolinska University Hospital; … |
| 2026-10-19 | [Towards understanding and monitorability of reasoning LLMs](https://doi.org/10.1038/s42256-026-01333-6) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) |  |  |
| 2026-10-16 | [Large-scale iontronic skins with neural-hierarchical processing architecture](https://doi.org/10.1038/s42256-026-01325-6) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | Zhibin Li, Bingxu Da, Junli Shi et al. | Southern University of Science and Technology; Beijing Institute of Technology; Mohamed bin Zayed University of Artificial Intelligence |
| 2026-10-13 | [An all-in-one foundation model for multimodal medical image restoration and enhancement](https://doi.org/10.1038/s42256-026-01310-z) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | Luyang Cao, Zhijian Wu, Jian Zhang et al. | Nanjing University; Westlake University; Southeast University; … |
| 2026-10-07 | [Characterizing the role of reasoning tokens in large language models as state over tokens](https://doi.org/10.1038/s42256-026-01303-y) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | Moshe Levy, Zohar Elyoseph, Shauli Ravfogel et al. | Bar-Ilan University; University of Haifa; New York University; … |
| 2026-10-07 | [Emotional optimization by newsroom AI needs behavioural evaluation](https://doi.org/10.1038/s42256-026-01315-8) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | Bence Bagó, Jean‐François Bonnefon | Tilburg University; Centre National de la Recherche Scientifique; Toulouse School of Economics |
| 2026-10-01 | [Large language models discover complementary heuristics for combinatorial optimization](https://doi.org/10.1038/s42256-026-01307-8) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | Huatian Gong, Shuaian Wang, Dong‐Ping Song et al. | Nanyang Technological University; Hong Kong Polytechnic University; University of Liverpool; … |
| 2026-10-01 | [Shifting from knowledge retrieval to evidence exploration and synthesis](https://doi.org/10.1038/s42256-026-01313-w) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | Shruti Shikhare, Jake Cohen-Setton, Krishna C. Bulusu | AstraZeneca (Spain); AstraZeneca (United Kingdom) |
| 2026-09-30 | [Towards foundation-style models for energy-frontier heterogeneous neutrino detectors via self-supervised pretraining](https://doi.org/10.1038/s42256-026-01309-6) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | S. Alonso Monsalve, Fabio Cufino, U. Köse et al. | ETH Zurich; Institute for Particle Physics and Astrophysics |
| 2026-09-28 | [Task-structured modularity emerges in artificial networks and aligns with brain architecture](https://doi.org/10.1038/s42256-026-01306-9) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | Yuhang Wu, Shikuang Deng, Kangrui Du et al. | University of Electronic Science and Technology of China; Zhejiang University; University of Pennsylvania; … |
| 2026-09-28 | [Minute-scale training for microrobot navigation](https://doi.org/10.1038/s42256-026-01305-w) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | Yinghan Sun, Aoji Zhu, Xiang Ji et al. | Hong Kong Polytechnic University; Chinese University of Hong Kong; Harbin Institute of Technology |
| 2026-09-28 | [Regional climate risk assessment from climate models using probabilistic machine learning](https://doi.org/10.1038/s42256-026-01308-7) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | Zhong Yi Wan, Ignacio Lopez‐Gomez, Robert W. Carver et al. | Google (United States); California Institute of Technology; General Motors (United States); … |

## Cite this page

Scholar4AI. (2026). Nature Machine Intelligence. Journal Research Rankings. Retrieved October 26, 2026, from https://scholar4ai.com/journals/nature-machine-intelligence

```bibtex
@misc{scholar4ai-journals-nature-machine-intelligence,
  author = {{Scholar4AI}},
  title = {Nature Machine Intelligence},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/journals/nature-machine-intelligence}},
  urldate = {2026-10-26},
  note = {Journal Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}
```

License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).