---
title: "EACL (A): papers and universities"
description: "EACL (European Association for Computational Linguistics) is rated A by the CORE Conference Rankings (ICORE2026); OpenAlex lists 891 of its papers from 2024–2026 (250 in 2024, 641 in 2026; 2025 not in OpenAlex yet). By the countries of the authors' institutions, the most papers come from the United States (257), Germany (112) and the United Kingdom (85)."
url: https://scholar4ai.com/proceedings/eacl
markdown_url: https://scholar4ai.com/proceedings/eacl.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "EACL (European Association for Computational Linguistics) is rated A by the CORE Conference Rankings (ICORE2026); OpenAlex lists 891 of its papers from 2024–2026 (250 in 2024, 641 in 2026; 2025 not in OpenAlex yet). (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)
---

# EACL: European Association for Computational Linguistics — papers and institutions, 2024–2026

Papers of EACL, European 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.

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

## Key findings

- EACL (European Association for Computational Linguistics) is rated A by the CORE Conference Rankings (ICORE2026); OpenAlex lists 891 of its papers from 2024–2026 (250 in 2024, 641 in 2026; 2025 not in OpenAlex yet).
- By the countries of the authors' institutions, the most papers come from the United States (257), Germany (112) and the United Kingdom (85).
- The institutions with the most papers are Amazon (United States) (19), Technische Universität Darmstadt (18) and Carnegie Mellon University (18).
- Its most-cited paper of these years is “RAGAs: Automated Evaluation of Retrieval Augmented Generation” (2024), with 665 citations.
- OpenAlex has affiliations for only 82% of its papers, so the institution and country counts are incomplete.

## Papers per year

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

| Year | Papers | With affiliations |
|---|---:|---:|
| 2024 | 250 | 231 |
| 2025 | – | – |
| 2026 | 641 | 503 |

## Sources

*Where OpenAlex lists the papers*

| OpenAlex source | Which papers |
|---|---|
| [S4306418011](https://openalex.org/S4306418011) | The conference's proceedings |

## Who publishes there

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

| # | Institution | Papers |
|---:|---|---:|
| 1 | Amazon (United States) | 19 |
| 2 | Technische Universität Darmstadt | 18 |
| 3 | Carnegie Mellon University | 18 |
| 4 | University of Edinburgh | 18 |
| 5 | [Centre National de la Recherche Scientifique](https://scholar4ai.com/institutions/centre-national-de-la-recherche-scientifique.md) | 16 |
| 6 | Mohamed bin Zayed University of Artificial Intelligence | 16 |
| 7 | Johns Hopkins University | 15 |
| 8 | University of Maryland, College Park | 15 |
| 9 | The University of Tokyo | 15 |
| 10 | University of Cambridge | 14 |

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

| # | Country | Papers |
|---:|---|---:|
| 1 | United States | 257 |
| 2 | Germany | 112 |
| 3 | United Kingdom | 85 |
| 4 | Japan | 50 |
| 5 | China | 49 |
| 6 | Canada | 42 |
| 7 | India | 35 |
| 8 | South Korea | 35 |
| 9 | Switzerland | 33 |
| 10 | Italy | 33 |

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

| # | Keyword | Papers |
|---:|---|---:|
| 1 | [large language models](https://scholar4ai.com/keywords/large-language-models.md) | 291 |
| 2 | low-resource languages | 43 |
| 3 | benchmark | 29 |
| 4 | retrieval-augmented generation | 29 |
| 5 | [vision-language models](https://scholar4ai.com/keywords/vision-language-models.md) | 28 |
| 6 | language models | 25 |
| 7 | chatbots | 19 |
| 8 | fine-tuning | 17 |
| 9 | machine translation | 17 |
| 10 | named entity recognition | 17 |

## Most-cited papers

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

| # | Citations | Title | Published | Authors |
|---:|---:|---|---|---|
| 1 | 665 | [RAGAs: Automated Evaluation of Retrieval Augmented Generation](https://doi.org/10.18653/v1/2024.eacl-demo.16) | 2024-01-01 | Shahul Es, Jithin James, Luis Espinosa-Anke et al. |
| 2 | 70 | [Leak, Cheat, Repeat: Data Contamination and Evaluation Malpractices in Closed-Source LLMs](https://doi.org/10.18653/v1/2024.eacl-long.5) | 2024-01-01 | Simone Balloccu, Patrícia Schmidtová, Mateusz Lango et al. |
| 3 | 44 | [Clever Hans or Neural Theory of Mind? Stress Testing Social Reasoning in Large Language Models](https://doi.org/10.18653/v1/2024.eacl-long.138) | 2024-01-01 | Natalie Shapira, Mosh Levy, Seyed Hossein Alavi et al. |
| 4 | 37 | [M4: Multi-generator, Multi-domain, and Multi-lingual Black-Box Machine-Generated Text Detection](https://doi.org/10.18653/v1/2024.eacl-long.83) | 2024-01-01 | Yuxia Wang, Jonibek Mansurov, Petar Ivanov et al. |
| 5 | 29 | [Learning to Retrieve In-Context Examples for Large Language Models](https://doi.org/10.18653/v1/2024.eacl-long.105) | 2024-01-01 | Liang Wang, Nan Yang, Furu Wei |
| 6 | 28 | [LAraBench: Benchmarking Arabic AI with Large Language Models](https://doi.org/10.18653/v1/2024.eacl-long.30) | 2024-01-01 | Ahmed Abdelalí, Hamdy Mubarak, Shammur Absar Chowdhury et al. |
| 7 | 27 | [MLCopilot: Unleashing the Power of Large Language Models in Solving Machine Learning Tasks](https://doi.org/10.18653/v1/2024.eacl-long.179) | 2024-01-01 | Lei Zhang, Yuge Zhang, Kan Ren et al. |
| 8 | 25 | [Generating Benchmarks for Factuality Evaluation of Language Models](https://doi.org/10.18653/v1/2024.eacl-long.4) | 2024-01-01 | Dor Muhlgay, Ori Ram, Inbal Magar et al. |
| 9 | 25 | [LLM Comparative Assessment: Zero-shot NLG Evaluation through Pairwise Comparisons using Large Language Models](https://doi.org/10.18653/v1/2024.eacl-long.8) | 2024-01-01 | Adian Liusie, Potsawee Manakul, Mark Gales |
| 10 | 24 | [MEGAnno+: A Human-LLM Collaborative Annotation System](https://doi.org/10.18653/v1/2024.eacl-demo.18) | 2024-01-01 | Hannah Kim, Kushan Mitra, Rafael Li Chen et al. |

## Cite this page

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

```bibtex
@misc{scholar4ai-proceedings-eacl,
  author = {{Scholar4AI}},
  title = {EACL: European Association for Computational Linguistics — papers and institutions, 2024–2026},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/proceedings/eacl}},
  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/).