---
title: "AAAI (A*): papers and universities"
description: "AAAI (National Conference of the American Association for Artificial Intelligence) is rated A* by the CORE Conference Rankings (ICORE2026); OpenAlex lists 11,266 of its papers from 2024–2026 (2,867 in 2024, 3,486 in 2025, 4,913 in 2026). By the countries of the authors' institutions, the most papers come from China (6,957), the United States (2,415) and Hong Kong (827)."
url: https://scholar4ai.com/proceedings/aaai
markdown_url: https://scholar4ai.com/proceedings/aaai.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "AAAI (National Conference of the American Association for Artificial Intelligence) is rated A* by the CORE Conference Rankings (ICORE2026); OpenAlex lists 11,266 of its papers from 2024–2026 (2,867 in 2024, 3,486 in… (as of 2026-11-02)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-11-02T12:20:52+09:00
window: 2026-10-04 to 2026-11-02
source: OpenAlex (CC0)
---

# AAAI: National Conference of the American Association for Artificial Intelligence — papers and institutions, 2024–2026

Papers of AAAI, National Conference of the American Association for Artificial Intelligence (CORE rank A*; field: Artificial intelligence, Computer vision and multimedia computation, Machine learning), 2024–2026: per year, the institutions, countries and topics, and the most-cited papers. Ranks are those of the CORE Conference Rankings, edition ICORE2026 (portal.core.edu.au), applied to every year shown. Papers are the works OpenAlex lists for the conference's proceedings, or for the issues of a conference-linked journal that publishes its papers (such as PACMPL, PVLDB or ACM TOG), by publication year; workshops, companion volumes, posters and Findings are left out. A paper counts once for each institution and country among its authors' affiliations as OpenAlex assigns them; papers without affiliations in OpenAlex count for none. For conferences published in book series that OpenAlex files as one source (LNCS, LIPIcs, SIAM and IOS Press proceedings), the papers are found by DOI: those of the volumes with the conference's title in Crossref, or LIPIcs DOIs, which name the conference. Conferences without DOIs (PMLR, USENIX, OpenReview) are listed without counts. A dash (–) for a year means OpenAlex has no papers of the conference for it yet: the proceedings are not published or indexed yet, or the conference did not meet that year (some meet every other year). 2026 counts what OpenAlex had indexed by 2026-11-02.

All conferences: https://scholar4ai.com/proceedings.md

## Key findings

- AAAI (National Conference of the American Association for Artificial Intelligence) is rated A* by the CORE Conference Rankings (ICORE2026); OpenAlex lists 11,266 of its papers from 2024–2026 (2,867 in 2024, 3,486 in 2025, 4,913 in 2026).
- By the countries of the authors' institutions, the most papers come from China (6,957), the United States (2,415) and Hong Kong (827).
- The institutions with the most papers are Chinese Academy of Sciences (596), Zhejiang University (541) and Tsinghua University (523).
- Its most-cited paper of these years is “T2I-Adapter: Learning Adapters to Dig Out More Controllable Ability for Text-to-Image Diffusion Models” (2024), with 957 citations.

## Papers per year

*AAAI papers per publication year in OpenAlex (–: not in OpenAlex yet)*

| Year | Papers | With affiliations |
|---|---:|---:|
| 2024 | 2,867 | 2,842 |
| 2025 | 3,486 | 3,459 |
| 2026 | 4,913 | 4,871 |

## Sources

*Where OpenAlex lists the papers*

| OpenAlex source | Which papers |
|---|---|
| [S4210191458](https://openalex.org/S4210191458) | The conference's proceedings |

## Who publishes there

*Institutions with the most AAAI papers, 2024–2026*

| # | Institution | Papers |
|---:|---|---:|
| 1 | [Chinese Academy of Sciences](https://scholar4ai.com/institutions/chinese-academy-of-sciences.md) | 596 |
| 2 | [Zhejiang University](https://scholar4ai.com/institutions/zhejiang-university.md) | 541 |
| 3 | [Tsinghua University](https://scholar4ai.com/institutions/tsinghua-university.md) | 523 |
| 4 | [University of Chinese Academy of Sciences](https://scholar4ai.com/institutions/university-of-chinese-academy-of-sciences.md) | 445 |
| 5 | [Peking University](https://scholar4ai.com/institutions/peking-university.md) | 414 |
| 6 | [Shanghai Jiao Tong University](https://scholar4ai.com/institutions/shanghai-jiao-tong-university.md) | 366 |
| 7 | [University of Science and Technology of China](https://scholar4ai.com/institutions/university-of-science-and-technology-of-china.md) | 332 |
| 8 | [Harbin Institute of Technology](https://scholar4ai.com/institutions/harbin-institute-of-technology.md) | 319 |
| 9 | [Nanyang Technological University](https://scholar4ai.com/institutions/nanyang-technological-university.md) | 314 |
| 10 | [National University of Singapore](https://scholar4ai.com/institutions/national-university-of-singapore.md) | 306 |

*Countries with the most AAAI papers, 2024–2026*

| # | Country | Papers |
|---:|---|---:|
| 1 | China | 6,957 |
| 2 | United States | 2,415 |
| 3 | Hong Kong | 827 |
| 4 | Singapore | 747 |
| 5 | United Kingdom | 686 |
| 6 | Australia | 481 |
| 7 | South Korea | 453 |
| 8 | Germany | 368 |
| 9 | Canada | 315 |
| 10 | Japan | 254 |

*Keywords with the most AAAI papers, 2024–2026*

| # | Keyword | Papers |
|---:|---|---:|
| 1 | [large language models](https://scholar4ai.com/keywords/large-language-models.md) | 1,341 |
| 2 | diffusion models | 428 |
| 3 | [graph neural networks](https://scholar4ai.com/keywords/graph-neural-networks.md) | 361 |
| 4 | [vision-language models](https://scholar4ai.com/keywords/vision-language-models.md) | 342 |
| 5 | [contrastive learning](https://scholar4ai.com/keywords/contrastive-learning.md) | 317 |
| 6 | [knowledge distillation](https://scholar4ai.com/keywords/knowledge-distillation.md) | 278 |
| 7 | multimodal large language models | 224 |
| 8 | [reinforcement learning](https://scholar4ai.com/keywords/reinforcement-learning.md) | 207 |
| 9 | interpretability | 205 |
| 10 | self-supervised learning | 163 |

## Most-cited papers

*Most-cited AAAI papers of 2024–2026 (citations counted by OpenAlex)*

| # | Citations | Title | Published | Authors |
|---:|---:|---|---|---|
| 1 | 957 | [T2I-Adapter: Learning Adapters to Dig Out More Controllable Ability for Text-to-Image Diffusion Models](https://doi.org/10.1609/aaai.v38i5.28226) | 2024-03-24 | Chong Mou, Xintao Wang, Liangbin Xie et al. |
| 2 | 558 | [Graph of Thoughts: Solving Elaborate Problems with Large Language Models](https://doi.org/10.1609/aaai.v38i16.29720) | 2024-03-24 | Maciej Besta, Nils Blach, Ales Kubicek et al. |
| 3 | 455 | [Benchmarking Large Language Models in Retrieval-Augmented Generation](https://doi.org/10.1609/aaai.v38i16.29728) | 2024-03-24 | Jiawei Chen, Hongyu Lin, Xianpei Han et al. |
| 4 | 382 | [U-KAN Makes Strong Backbone for Medical Image Segmentation and Generation](https://doi.org/10.1609/aaai.v39i5.32491) | 2025-04-11 | Chenxin Li, Xinyu Liu, Wuyang Li et al. |
| 5 | 315 | [AnomalyGPT: Detecting Industrial Anomalies Using Large Vision-Language Models](https://doi.org/10.1609/aaai.v38i3.27963) | 2024-03-24 | Zhaopeng Gu, Bingke Zhu, Guibo Zhu et al. |
| 6 | 313 | [Omni-Kernel Network for Image Restoration](https://doi.org/10.1609/aaai.v38i2.27907) | 2024-03-24 | Yuning Cui, Wenqi Ren, Alois Knoll |
| 7 | 280 | [MedSegDiff-V2: Diffusion-Based Medical Image Segmentation with Transformer](https://doi.org/10.1609/aaai.v38i6.28418) | 2024-03-24 | Junde Wu, Wei Ji, Huazhu Fu et al. |
| 8 | 256 | [MSGNet: Learning Multi-Scale Inter-series Correlations for Multivariate Time Series Forecasting](https://doi.org/10.1609/aaai.v38i10.28991) | 2024-03-24 | Wanlin Cai, Yuxuan Liang, Xianggen Liu et al. |
| 9 | 253 | [MemoryBank: Enhancing Large Language Models with Long-Term Memory](https://doi.org/10.1609/aaai.v38i17.29946) | 2024-03-24 | Wanjun Zhong, Lianghong Guo, Qiqi Gao et al. |
| 10 | 236 | [Pinwheel-shaped Convolution and Scale-based Dynamic Loss for Infrared Small Target Detection](https://doi.org/10.1609/aaai.v39i9.32996) | 2025-04-11 | Jiangnan Yang, Shuangli Liu, Jingjun Wu et al. |

## Cite this page

Scholar4AI. (2026). AAAI: National Conference of the American Association for Artificial Intelligence — papers and institutions, 2024–2026. Journal and Conference Research Rankings. Retrieved November 2, 2026, from https://scholar4ai.com/proceedings/aaai

```bibtex
@misc{scholar4ai-proceedings-aaai,
  author = {{Scholar4AI}},
  title = {AAAI: National Conference of the American Association for Artificial Intelligence — papers and institutions, 2024–2026},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/proceedings/aaai}},
  urldate = {2026-11-02},
  note = {Journal and Conference 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/).