Scholar4AI Updated 2026-11-02 12:20 UTC+09:00

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. Also as Markdown.

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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)
YearPapersWith affiliations
20242,8672,842
20253,4863,459
20264,9134,871

Sources#

Where OpenAlex lists the papers
OpenAlex sourceWhich papers
S4210191458The conference's proceedings

Who publishes there#

Countries with the most AAAI papers, 2024–2026
#CountryPapers
1China6,957
2United States2,415
3Hong Kong827
4Singapore747
5United Kingdom686
6Australia481
7South Korea453
8Germany368
9Canada315
10Japan254
Keywords with the most AAAI papers, 2024–2026
#KeywordPapers
1large language models1,341
2diffusion models428
3graph neural networks361
4vision-language models342
5contrastive learning317
6knowledge distillation278
7multimodal large language models224
8reinforcement learning207
9interpretability205
10self-supervised learning163

Most-cited papers#

Most-cited AAAI papers of 2024–2026 (citations counted by OpenAlex)
#CitationsTitlePublishedAuthors
1957T2I-Adapter: Learning Adapters to Dig Out More Controllable Ability for Text-to-Image Diffusion Models2024-03-24Chong Mou, Xintao Wang, Liangbin Xie et al.
2558Graph of Thoughts: Solving Elaborate Problems with Large Language Models2024-03-24Maciej Besta, Nils Blach, Ales Kubicek et al.
3455Benchmarking Large Language Models in Retrieval-Augmented Generation2024-03-24Jiawei Chen, Hongyu Lin, Xianpei Han et al.
4382U-KAN Makes Strong Backbone for Medical Image Segmentation and Generation2025-04-11Chenxin Li, Xinyu Liu, Wuyang Li et al.
5315AnomalyGPT: Detecting Industrial Anomalies Using Large Vision-Language Models2024-03-24Zhaopeng Gu, Bingke Zhu, Guibo Zhu et al.
6313Omni-Kernel Network for Image Restoration2024-03-24Yuning Cui, Wenqi Ren, Alois Knoll
7280MedSegDiff-V2: Diffusion-Based Medical Image Segmentation with Transformer2024-03-24Junde Wu, Wei Ji, Huazhu Fu et al.
8256MSGNet: Learning Multi-Scale Inter-series Correlations for Multivariate Time Series Forecasting2024-03-24Wanlin Cai, Yuxuan Liang, Xianggen Liu et al.
9253MemoryBank: Enhancing Large Language Models with Long-Term Memory2024-03-24Wanjun Zhong, Lianghong Guo, Qiqi Gao et al.
10236Pinwheel-shaped Convolution and Scale-based Dynamic Loss for Infrared Small Target Detection2025-04-11Jiangnan Yang, Shuangli Liu, Jingjun Wu et al.

Conferences in the same field#

NeurIPS · EMNLP · ACL · CVPR · ICRA · ECCV · IJCAI · KDD · ACMMM · ICCV · HRI · SIGGRAPH Asia · EC · SIGGRAPH · ICDM · KR · ICAPS · IROS · MICCAI · WACV · Interspeech · ICME · NAACL · AAMAS · CIKM · ECAI · EACL · ECML PKDD · WSDM · GECCO · SIGSPATIAL · PPSN · MMSys · IJCAR · CP · SAT · CADE · FOGA

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

@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}
}

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