ACL: Association for Computational Linguistics — papers and institutions, 2024–2026

Papers of ACL, Association for Computational Linguistics (CORE rank A*; field: 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#

ACL (Association for Computational Linguistics) is rated A* by the CORE Conference Rankings (ICORE2026); OpenAlex lists 5,662 of its papers from 2024–2026 (1,036 in 2024, 1,971 in 2025, 2,655 in 2026).
By the countries of the authors' institutions, the most papers come from China (2,419), the United States (1,523) and Hong Kong (394).
The institutions with the most papers are Tsinghua University (294), Peking University (245) and Zhejiang University (238).
Its most-cited paper of these years is “ChatDev: Communicative Agents for Software Development” (2024), with 450 citations.
OpenAlex has affiliations for only 87% of its papers, so the institution and country counts are incomplete.

Papers per year#

ACL papers per publication year in OpenAlex (–: not in OpenAlex yet)
Year	Papers	With affiliations
2024	1,036	929
2025	1,971	1,715
2026	2,655	2,277

Sources#

Where OpenAlex lists the papers
OpenAlex source	Which papers
S4393915740	The conference's proceedings

Who publishes there#

Institutions with the most ACL papers, 2024–2026
#	Institution	Papers
1	Tsinghua University	294
2	Peking University	245
3	Zhejiang University	238
4	Chinese Academy of Sciences	225
5	University of Chinese Academy of Sciences	199
6	Harbin Institute of Technology	177
7	Alibaba Group (China)	156
8	National University of Singapore	155
9	Shanghai Jiao Tong University	155
10	Fudan University	149

Countries with the most ACL papers, 2024–2026
#	Country	Papers
1	China	2,419
2	United States	1,523
3	Hong Kong	394
4	United Kingdom	335
5	Singapore	311
6	Germany	270
7	South Korea	248
8	Canada	173
9	Australia	171
10	Japan	161

Keywords with the most ACL papers, 2024–2026
#	Keyword	Papers
1	large language models	2,415
2	retrieval-augmented generation	235
3	benchmark	207
4	vision-language models	163
5	low-resource languages	152
6	multimodal large language models	147
7	LLM agents	125
8	benchmarking	120
9	knowledge distillation	120
10	reinforcement learning	115

Most-cited papers#

Most-cited ACL papers of 2024–2026 (citations counted by OpenAlex)
#	Citations	Title	Published	Authors
1	450	ChatDev: Communicative Agents for Software Development	2024-01-01	Chen Qian, Wei Liu, Hongzhang Liu et al.
2	444	Video-ChatGPT: Towards Detailed Video Understanding via Large Vision and Language Models	2024-01-01	Muhammad Maaz, Hanoona Rasheed, Salman Hameed Khan et al.
3	434	LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models	2024-01-01	Yaowei Zheng, Richong Zhang, Junhao Zhang et al.
4	294	DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models	2024-01-01	Damai Dai, Chengqi Deng, Chenggang Zhao et al.
5	216	Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference	2025-01-01	Benjamin C. Warner, Antoine Chaffin, Benjamin Clavié et al.
6	186	LongBench: A Bilingual, Multitask Benchmark for Long Context Understanding	2024-01-01	Yushi Bai, Xin Lv, Jiajie Zhang et al.
7	150	Improving Text Embeddings with Large Language Models	2024-01-01	Liang Wang, Nan Yang, Xiaolong Huang et al.
8	138	Large Language Models are not Fair Evaluators	2024-01-01	Peiyi Wang, Lei Li, Liang Chen et al.
9	119	Same Task, More Tokens: the Impact of Input Length on the Reasoning Performance of Large Language Models	2024-01-01	Mosh Levy, Alon Jacoby, Yoav Goldberg
10	119	RAGTruth: A Hallucination Corpus for Developing Trustworthy Retrieval-Augmented Language Models	2024-01-01	Cheng Niu, Yuanhao Wu, Juno Zhu et al.

Conferences in the same field#

AAAI · EMNLP · ICRA · IJCAI · HRI · EC · KR · ICAPS · IROS · Interspeech · NAACL · AAMAS · CIKM · ECAI · EACL · GECCO · IJCAR · CP · SAT · CADE · FOGA

Cite this page

Scholar4AI. (2026). ACL: Association for Computational Linguistics — papers and institutions, 2024–2026. Journal and Conference Research Rankings. Retrieved November 2, 2026, from https://scholar4ai.com/proceedings/acl

@misc{scholar4ai-proceedings-acl,
  author = {{Scholar4AI}},
  title = {ACL: Association for Computational Linguistics — papers and institutions, 2024–2026},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/proceedings/acl}},
  urldate = {2026-11-02},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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