---
title: "Findings of the Association for Computational Linguistics"
description: "Findings of the Association for Computational Linguistics: 233 works in the Elamur Research library (2020–2026), 37,840 citations; its topics, authors…"
canonical: "https://research.elamur.ai/free/en/venues/findings/"
---
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# Findings of the Association for Computational Linguistics

Conference series Published by [Association for Computational Linguistics](https://md.research.elamur.ai/free/en/publishers/association-for-computational-linguistics/)

- [ACL Anthology](https://aclanthology.org/venues/findings/)
- [OpenAlex](https://openalex.org/S4363605604)

[**233** works in our library](https://md.research.elamur.ai/free/en/venues/findings/works/) · [**37,840** citations of these works](https://md.research.elamur.ai/free/en/venues/findings/works/) · [**17,405** citations in our library](https://md.research.elamur.ai/free/en/venues/findings/works/) · [**2020–2026** years of the works here](#years)

## Works by year

Works in our library by year 233 dated works from 2020 to 2026; the busiest year is 2023 with 71.

**The numbers**

| Year | Works |
| --- | --- |
| 2026 | 24 |
| 2025 | 13 |
| 2024 | 35 |
| 2023 | 71 |
| 2022 | 28 |
| 2021 | 29 |
| 2020 | 33 |

## Top topics

Topics of its works in our library, with the number of works on each.

[Language models & pretraining (61)](https://md.research.elamur.ai/free/en/topics/language-models/) · [Evaluation & benchmarks (35)](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) · [Reasoning (26)](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Semitic languages (24)](https://md.research.elamur.ai/free/en/topics/semitic-languages/) · [Machine translation (21)](https://md.research.elamur.ai/free/en/topics/machine-translation/) · [English (21)](https://md.research.elamur.ai/free/en/topics/english/) · [Sentiment & emotion (20)](https://md.research.elamur.ai/free/en/topics/sentiment-emotion/) · [Hebrew & Aramaic (18)](https://md.research.elamur.ai/free/en/topics/hebrew-aramaic/) · [Discourse analysis (15)](https://md.research.elamur.ai/free/en/topics/discourse-analysis/) · [Multilingual & cross-lingual NLP (14)](https://md.research.elamur.ai/free/en/topics/multilingual-nlp/) · [Dialogue systems (13)](https://md.research.elamur.ai/free/en/topics/dialogue-systems/) · [Modern Hebrew (13)](https://md.research.elamur.ai/free/en/topics/modern-hebrew/) · [Coreference resolution (12)](https://md.research.elamur.ai/free/en/topics/coreference-resolution/) · [Bias, fairness & safety (11)](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/) · [Vision & language (8)](https://md.research.elamur.ai/free/en/topics/multimodal/)

**27 more topics**

[Low-resource languages (7)](https://md.research.elamur.ai/free/en/topics/low-resource-languages/) · [Question answering (6)](https://md.research.elamur.ai/free/en/topics/question-answering/) · [Summarization (6)](https://md.research.elamur.ai/free/en/topics/summarization/) · [Morphology (5)](https://md.research.elamur.ai/free/en/topics/morphology/) · [Information retrieval & search (5)](https://md.research.elamur.ai/free/en/topics/information-retrieval/) · [Idioms & multiword expressions (5)](https://md.research.elamur.ai/free/en/topics/multiword-expressions/) · [Biblical Hebrew (5)](https://md.research.elamur.ai/free/en/topics/biblical-hebrew/) · [Speech act theory (4)](https://md.research.elamur.ai/free/en/topics/speech-act-theory/) · [Text generation (4)](https://md.research.elamur.ai/free/en/topics/text-generation/) · [Legal AI (4)](https://md.research.elamur.ai/free/en/topics/legal-ai/) · [Tokenization & segmentation (4)](https://md.research.elamur.ai/free/en/topics/tokenization/) · [Implicature (3)](https://md.research.elamur.ai/free/en/topics/implicature/) · [Dependency parsing (3)](https://md.research.elamur.ai/free/en/topics/dependency-parsing/) · [Speech & spoken language (3)](https://md.research.elamur.ai/free/en/topics/speech/) · [Semantic parsing & meaning representation (3)](https://md.research.elamur.ai/free/en/topics/semantic-parsing/) · [Efficient models & compression (3)](https://md.research.elamur.ai/free/en/topics/efficient-models/) · [Named entity recognition (2)](https://md.research.elamur.ai/free/en/topics/named-entity-recognition/) · [Universal Dependencies (2)](https://md.research.elamur.ai/free/en/topics/universal-dependencies/) · [Knowledge graphs & ontologies (2)](https://md.research.elamur.ai/free/en/topics/knowledge-graphs/) · [Code & programming languages (2)](https://md.research.elamur.ai/free/en/topics/code-and-programming/) · [Grammatical error correction & learner language (2)](https://md.research.elamur.ai/free/en/topics/grammatical-error-correction/) · [Aramaic (2)](https://md.research.elamur.ai/free/en/topics/aramaic/) · [Word sense disambiguation (1)](https://md.research.elamur.ai/free/en/topics/word-sense-disambiguation/) · [Treebanks (1)](https://md.research.elamur.ai/free/en/topics/treebanks/) · [Semantic role labeling (1)](https://md.research.elamur.ai/free/en/topics/semantic-role-labeling/) · [Information extraction (1)](https://md.research.elamur.ai/free/en/topics/information-extraction/) · [French (1)](https://md.research.elamur.ai/free/en/topics/french/)

## Fields

[Computer Science (232)](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Arts and Humanities (215)](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Social Sciences (30)](https://md.research.elamur.ai/free/en/shelves/social-sciences/) · [Psychology (9)](https://md.research.elamur.ai/free/en/shelves/psychology/) · [Medicine (5)](https://md.research.elamur.ai/free/en/shelves/medicine/) · [Engineering (1)](https://md.research.elamur.ai/free/en/shelves/engineering/) · [Mathematics (1)](https://md.research.elamur.ai/free/en/shelves/mathematics/)

## Top authors

Authors with a page who published here most often: their works here, and the citations of those works.

[🧑‍🔬**Reut Tsarfaty**9 works here · 588 citations](https://md.research.elamur.ai/free/en/authors/reut-tsarfaty/) · [🧑‍🔬**Preslav Nakov**5 works here · 864 citations](https://md.research.elamur.ai/free/en/authors/preslav-nakov/) · [🧑‍🔬**Daniel Khashabi**4 works here · 1,743 citations](https://md.research.elamur.ai/free/en/authors/daniel-khashabi/) · [🧑‍🔬**Hannaneh Hajishirzi**4 works here · 1,730 citations](https://md.research.elamur.ai/free/en/authors/hannaneh-hajishirzi/) · [🧑‍🔬**Nizar Habash**4 works here · 151 citations](https://md.research.elamur.ai/free/en/authors/nizar-habash/) · [🧑‍🔬**Nan Duan**3 works here · 3,968 citations](https://md.research.elamur.ai/free/en/authors/nan-duan/) · [🧑‍🔬**Noah A. Smith**3 works here · 1,941 citations](https://md.research.elamur.ai/free/en/authors/noah-a-smith/) · [🧑‍🔬**Yejin Choi**3 works here · 1,707 citations](https://md.research.elamur.ai/free/en/authors/yejin-choi/) · [🧑‍🔬**Shafiq Joty**3 works here · 1,386 citations](https://md.research.elamur.ai/free/en/authors/shafiq-joty/) · [🧑‍🔬**Sameer Singh**3 works here · 897 citations](https://md.research.elamur.ai/free/en/authors/sameer-singh/) · [🧑‍🔬**Yangqiu Song**3 works here · 435 citations](https://md.research.elamur.ai/free/en/authors/yangqiu-song/) · [🧑‍🔬**Wenhu Chen**3 works here · 386 citations](https://md.research.elamur.ai/free/en/authors/wenhu-chen/)

## Top institutions

Institutions on the bylines of its works here, by the number of works.

[🔬**Allen Institute for Artificial Intelligence** Seattle · United States 15 works here](https://md.research.elamur.ai/free/en/labs/allen-institute-for-artificial-intelligence/) · [🏢**Google** Mountain View · United States 12 works here](https://md.research.elamur.ai/free/en/companies/google/) · [🎓**Nanyang Technological University** Singapore · Singapore 11 works here](https://md.research.elamur.ai/free/en/universities/nanyang-technological-university/) · [🎓**University of Washington** Seattle · United States 11 works here](https://md.research.elamur.ai/free/en/universities/university-of-washington/) · [🏢**Microsoft** Redmond · United States 9 works here](https://md.research.elamur.ai/free/en/companies/microsoft/) · [🎓**Bar-Ilan University** Ramat Gan · Israel 9 works here](https://md.research.elamur.ai/free/en/universities/bar-ilan-university/) · [🎓**Harbin Institute of Technology** Harbin · China 8 works here](https://md.research.elamur.ai/free/en/universities/harbin-institute-of-technology/) · [🎓**Stanford University** Stanford · United States 8 works here](https://md.research.elamur.ai/free/en/universities/stanford-university/) · [🎓**Carnegie Mellon University** Pittsburgh · United States 7 works here](https://md.research.elamur.ai/free/en/universities/carnegie-mellon-university/) · [🎓**Hebrew University of Jerusalem** Jerusalem · Israel 6 works here](https://md.research.elamur.ai/free/en/universities/hebrew-university-of-jerusalem/) · [🎓**Zhejiang University** Hangzhou · China 6 works here](https://md.research.elamur.ai/free/en/universities/zhejiang-university/) · [🎓**The University of Texas at Austin** Austin · United States 6 works here](https://md.research.elamur.ai/free/en/universities/the-university-of-texas-at-austin/)

## Works in our library (233)

The most cited first (OpenAlex citations plus our library's).

1. [**CodeBERT: A Pre-Trained Model for Programming and Natural Languages**Zhangyin Feng, Daya Guo, Duyu Tang, et al.*2020 · 2,954 citations*](https://md.research.elamur.ai/free/en/papers/feng-2020-codebert-pre-trained-model-programming/)
2. [**LEGAL-BERT: The Muppets straight out of Law School**Ilias Chalkidis, Manos Fergadiotis, Prodromos Malakasiotis, et al.*2020 · 1,490 citations*](https://md.research.elamur.ai/free/en/papers/chalkidis-2020-legal-bert-muppets-straight-out/)
3. [**RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language Models**Samuel Gehman, Suchin Gururangan, Maarten Sap, et al.*2020 · 1,277 citations*](https://md.research.elamur.ai/free/en/papers/gehman-2020-realtoxicityprompts-evaluating-neural-toxic-degeneration/)
4. [**Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them**Mirac Suzgun, Nathan Scales, Nathanael Schärli, et al.*2023 · 1,094 citations*](https://md.research.elamur.ai/free/en/papers/suzgun-2023-challenging-big-bench-tasks-whether/)
5. [**UNIFIEDQA: Crossing Format Boundaries with a Single QA System**Daniel Khashabi, Sewon Min, Tushar Khot, et al.*2020 · 843 citations*](https://md.research.elamur.ai/free/en/papers/khashabi-2020-unifiedqa-crossing-format-boundaries-single/)
6. [**Towards Reasoning in Large Language Models: A Survey**Jie Huang, Kevin Chen-Chuan Chang*2023 · 775 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-reasoning-large-language-models-survey/)
7. [**ChartQA: A Benchmark for Question Answering about Charts with Visual and Logical Reasoning**Ahmed Masry, Do Xuan Long, Jia Qing Tan, et al.*2022 · 744 citations*](https://md.research.elamur.ai/free/en/papers/masry-2022-chartqa-benchmark-question-answering-about/)
8. [**IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks and Pre-trained Multilingual Language Models for Indian Languages**Divyanshu Kakwani, Anoop Kunchukuttan, Satish Golla, et al.*2020 · 730 citations*](https://md.research.elamur.ai/free/en/papers/kakwani-2020-indicnlpsuite-monolingual-corpora-evaluation-benchmarks/)
9. [**Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes**Cheng-Yu Hsieh, Chun-Liang Li, Chih-kuan Yeh, et al.*2023 · 684 citations*](https://md.research.elamur.ai/free/en/papers/hsieh-2023-distilling-step-step-outperforming-larger/)
10. [**Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models**Jianmo Ni, Gustavo Hernandez Abrego, Noah Constant, et al.*2021 · 582 citations*](https://md.research.elamur.ai/free/en/papers/ni-2021-sentence-t5-scalable-sentence-encoders/)
11. [**PhoBERT: Pre-trained language models for Vietnamese**Dat Quoc Nguyen, Anh Tuan Nguyen*2020 · 571 citations*](https://md.research.elamur.ai/free/en/papers/nguyen-2020-phobert-pre-trained-language-models/)
12. [**AGIEval: A Human-Centric Benchmark for Evaluating Foundation Models**Wanjun Zhong, Ruixiang Cui, Yiduo Guo, et al.*2024 · 563 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2024-agieval-human-centric-benchmark-evaluating/)
13. [**Document Ranking with a Pretrained Sequence-to-Sequence Model**Rodrigo Nogueira, Zhiying Jiang, Ronak Pradeep, et al.*2020 · 538 citations*](https://md.research.elamur.ai/free/en/papers/nogueira-2020-document-ranking-pretrained-sequence-sequence/)
14. [**Evaluating Models' Local Decision Boundaries via Contrast Sets**Matt Gardner, Yoav Artzi, Victoria Basmov, et al.*2020 · 520 citations*](https://md.research.elamur.ai/free/en/papers/gardner-2020-evaluating-models-local-decision-boundaries/)
15. [**Sentiment Analysis in the Era of Large Language Models: A Reality Check**Wenxuan Zhang, Yue Deng, Bing Liu, et al.*2023 · 505 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-sentiment-analysis-era-large-language/)
16. [**Multilingual Machine Translation with Large Language Models: Empirical Results and Analysis**Wenhao Zhu, Hongyi Liu, Qingxiu Dong, et al.*2024 · 503 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2024-multilingual-machine-translation-large-language/)
17. [**BBQ: A hand-built bias benchmark for question answering**Alicia Parrish, Angelica Chen, Nikita Nangia, et al.*2022 · 487 citations*](https://md.research.elamur.ai/free/en/papers/parrish-2022-bbq-hand-built-bias-benchmark/)
18. [**ProphetNet: Predicting Future N-gram for Sequence-to-SequencePre-training**Weizhen Qi, Yu Yan, Yeyun Gong, et al.*2020 · 451 citations*](https://md.research.elamur.ai/free/en/papers/qi-2020-prophetnet-predicting-future-n-gram/)
19. [**GeDi: Generative Discriminator Guided Sequence Generation**Ben Krause, Akhilesh Deepak Gotmare, Bryan McCann, et al.*2021 · 444 citations*](https://md.research.elamur.ai/free/en/papers/krause-2021-gedi-generative-discriminator-guided-sequence/)
20. [**GPT-NER: Named Entity Recognition via Large Language Models**Shuhe Wang, Xiaofei Sun, Xiaoya Li, et al.*2025 · 436 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-gpt-ner-named-entity-recognition/)
21. [**Benchmarking Retrieval-Augmented Generation for Medicine**Guangzhi Xiong, Qiao Jin, Zhiyong Lu, et al.*2024 · 426 citations*](https://md.research.elamur.ai/free/en/papers/xiong-2024-benchmarking-retrieval-augmented-generation-medicine/)
22. [**The Internal State of an LLM Knows When It's Lying**Amos Azaria, Tom Mitchell*2023 · 425 citations*](https://md.research.elamur.ai/free/en/papers/azaria-2023-internal-state-llm-knows-when/)
23. [**Template-Based Named Entity Recognition Using BART**Leyang Cui, Yu Wu, Jian Liu, et al.*2021 · 420 citations*](https://md.research.elamur.ai/free/en/papers/cui-2021-template-based-named-entity-recognition/)
24. [**ChatGPT Beyond English: Towards a Comprehensive Evaluation of Large Language Models in Multilingual Learning**Viet Dac Lai, Nghia Ngo, Amir Pouran Ben Veyseh, et al.*2023 · 418 citations*](https://md.research.elamur.ai/free/en/papers/lai-2023-chatgpt-beyond-english-comprehensive-evaluation/)
25. [**BioMistral: A Collection of Open-Source Pretrained Large Language Models for Medical Domains**Yanis Labrak, Adrien Bazoge, Emmanuel Morin, et al.*2024 · 406 citations*](https://md.research.elamur.ai/free/en/papers/labrak-2024-biomistral-collection-open-source-pretrained/)

[See all 233 works →](https://md.research.elamur.ai/free/en/venues/findings/works/)

Venues, publishers and identifiers from OpenAlex (2026-10-14) and the ACL Anthology; yearly proceedings are counted as one series.