CIKM: ACM International Conference on Information and Knowledge Management — papers and institutions, 2024–2026

Papers of CIKM, ACM International Conference on Information and Knowledge Management (CORE rank A; field: Data management and data science, Artificial intelligence), 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#

CIKM (ACM International Conference on Information and Knowledge Management) is rated A by the CORE Conference Rankings (ICORE2026); OpenAlex lists 1,549 of its papers from 2024–2026 (697 in 2024, 852 in 2025; 2026 not in OpenAlex yet).
By the countries of the authors' institutions, the most papers come from China (745), the United States (379) and South Korea (153).
The institutions with the most papers are Chinese Academy of Sciences (50), Renmin University of China (48) and Tsinghua University (43).
Its most-cited paper of these years is “RCAgent: Cloud Root Cause Analysis by Autonomous Agents with Tool-Augmented Large Language Models” (2024), with 100 citations.

Papers per year#

CIKM papers per publication year in OpenAlex (–: not in OpenAlex yet)
Year	Papers	With affiliations
2024	697	683
2025	852	837
2026	–	–

Sources#

Where OpenAlex lists the papers
OpenAlex source	Which papers
S4393918199	The conference's proceedings

Who publishes there#

Institutions with the most CIKM papers, 2024–2026
#	Institution	Papers
1	Chinese Academy of Sciences	50
2	Renmin University of China	48
3	Tsinghua University	43
4	University of Science and Technology of China	42
5	Fudan University	40
6	Zhejiang University	36
7	University of Chinese Academy of Sciences	35
8	Amazon (United States)	33
9	Peking University	33
10	Beihang University	33

Countries with the most CIKM papers, 2024–2026
#	Country	Papers
1	China	745
2	United States	379
3	South Korea	153
4	Australia	129
5	Hong Kong	92
6	Germany	50
7	Canada	48
8	Singapore	48
9	United Kingdom	46
10	Italy	33

Keywords with the most CIKM papers, 2024–2026
#	Keyword	Papers
1	large language models	281
2	graph neural networks	104
3	recommender systems	90
4	contrastive learning	66
5	retrieval-augmented generation	54
6	knowledge graphs	35
7	knowledge distillation	30
8	interpretability	28
9	sequential recommendation	27
10	attention mechanism	26

Most-cited papers#

Most-cited CIKM papers of 2024–2026 (citations counted by OpenAlex)
#	Citations	Title	Published	Authors
1	100	RCAgent: Cloud Root Cause Analysis by Autonomous Agents with Tool-Augmented Large Language Models	2024-10-20	Zefan Wang, Z.G Liu, Y. Zhang et al.
2	67	Let Silence Speak: Enhancing Fake News Detection with Generated Comments from Large Language Models	2024-10-20	Qiong Nan, Qiang Sheng, Juan Cao et al.
3	66	Learnable Item Tokenization for Generative Recommendation	2024-10-20	Wenjie Wang, Honghui Bao, Xinyu Lin et al.
4	51	RecDiff: Diffusion Model for Social Recommendation	2024-10-20	Zongwei Li, Lianghao Xia, Chao Huang
5	51	Multivariate Time-Series Anomaly Detection based on Enhancing Graph Attention Networks with Topological Analysis	2024-10-20	Zhe Liu, Xiang Huang, Jingyun Zhang et al.
6	48	AlignRec: Aligning and Training in Multimodal Recommendations	2024-10-20	Yifan Liu, Kangning Zhang, Xiangyuan Ren et al.
7	46	LawLLM: Law Large Language Model for the US Legal System	2024-10-20	Dong Shu, Haoran Zhao, Xukun Liu et al.
8	42	Context Matters: Enhancing Sequential Recommendation with Context-aware Diffusion-based Contrastive Learning	2024-10-20	Ziqiang Cui, Haolun Wu, Bowei He et al.
9	40	Multi-Behavior Generative Recommendation	2024-10-20	Zihan Liu, Yupeng Hou, Julian McAuley
10	40	TWIN V2: Scaling Ultra-Long User Behavior Sequence Modeling for Enhanced CTR Prediction at Kuaishou	2024-10-20	Zihua Si, Lin Guan, Zhongxiang Sun et al.

Conferences in the same field#

AAAI · EMNLP · ACL · ICRA · IJCAI · KDD · WWW · SIGIR · VLDB · ICDE · HRI · SIGMOD · EC · ICDM · KR · ICAPS · PODS · IROS · Interspeech · NAACL · AAMAS · ECAI · EACL · ECML PKDD · RecSys · ECIR · WSDM · ICWSM · GECCO · ICDAR · MSR · SIGSPATIAL · ISWC · SDM · CAiSE · IJCAR · CP · ICDT · SAT · ER · CADE · FOGA

Cite this page

Scholar4AI. (2026). CIKM: ACM International Conference on Information and Knowledge Management — papers and institutions, 2024–2026. Journal and Conference Research Rankings. Retrieved November 2, 2026, from https://scholar4ai.com/proceedings/cikm

@misc{scholar4ai-proceedings-cikm,
  author = {{Scholar4AI}},
  title = {CIKM: ACM International Conference on Information and Knowledge Management — papers and institutions, 2024–2026},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/proceedings/cikm}},
  urldate = {2026-11-02},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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