---
title: "Transactions of the Association for Computational"
description: "Transactions of the Association for Computational Linguistics (TACL): 132 works in the Elamur Research library (2013–2026), 51,716 citations; its topics…"
canonical: "https://research.elamur.ai/free/en/venues/tacl/"
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# Transactions of the Association for Computational Linguistics (TACL)

Journal Published by [The MIT Press](https://md.research.elamur.ai/free/en/publishers/the-mit-press/)

- [Website](https://www.mitpressjournals.org/loi/tacl)
- [ACL Anthology](https://aclanthology.org/venues/tacl/)
- [OpenAlex](https://openalex.org/S2729999759)
- [Wikidata](https://www.wikidata.org/wiki/Q28736261)
- [ISSN 2307-387X](https://portal.issn.org/resource/ISSN/2307-387X)

[**132** works in our library](https://md.research.elamur.ai/free/en/venues/tacl/works/) · [**51,716** citations of these works](https://md.research.elamur.ai/free/en/venues/tacl/works/) · [**21,532** citations in our library](https://md.research.elamur.ai/free/en/venues/tacl/works/) · [**2013–2026** years of the works here](#years)

## Works by year

Works in our library by year 132 dated works from 2013 to 2026; the busiest year is 2021 with 19.

**The numbers**

| Year | Works |
| --- | --- |
| 2026 | 5 |
| 2024 | 9 |
| 2023 | 16 |
| 2022 | 10 |
| 2021 | 19 |
| 2020 | 13 |
| 2019 | 11 |
| 2018 | 12 |
| 2017 | 7 |
| 2016 | 10 |
| 2015 | 9 |
| 2014 | 8 |
| 2013 | 3 |

## Top topics

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

[Machine translation (18)](https://md.research.elamur.ai/free/en/topics/machine-translation/) · [Language models & pretraining (13)](https://md.research.elamur.ai/free/en/topics/language-models/) · [English (12)](https://md.research.elamur.ai/free/en/topics/english/) · [Multilingual & cross-lingual NLP (11)](https://md.research.elamur.ai/free/en/topics/multilingual-nlp/) · [Evaluation & benchmarks (10)](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) · [Question answering (8)](https://md.research.elamur.ai/free/en/topics/question-answering/) · [Coreference resolution (7)](https://md.research.elamur.ai/free/en/topics/coreference-resolution/) · [Syntax & grammar formalisms (6)](https://md.research.elamur.ai/free/en/topics/syntax-grammar/) · [Dialogue systems (5)](https://md.research.elamur.ai/free/en/topics/dialogue-systems/) · [Morphology (5)](https://md.research.elamur.ai/free/en/topics/morphology/) · [Reasoning (5)](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Semantic parsing & meaning representation (5)](https://md.research.elamur.ai/free/en/topics/semantic-parsing/) · [Psycholinguistics & language acquisition (5)](https://md.research.elamur.ai/free/en/topics/psycholinguistics/) · [Semitic languages (4)](https://md.research.elamur.ai/free/en/topics/semitic-languages/) · [Idioms & multiword expressions (4)](https://md.research.elamur.ai/free/en/topics/multiword-expressions/)

**25 more topics**

[Named entity recognition (3)](https://md.research.elamur.ai/free/en/topics/named-entity-recognition/) · [Discourse analysis (3)](https://md.research.elamur.ai/free/en/topics/discourse-analysis/) · [Dependency parsing (3)](https://md.research.elamur.ai/free/en/topics/dependency-parsing/) · [Universal Dependencies (3)](https://md.research.elamur.ai/free/en/topics/universal-dependencies/) · [Text generation (3)](https://md.research.elamur.ai/free/en/topics/text-generation/) · [Hebrew & Aramaic (3)](https://md.research.elamur.ai/free/en/topics/hebrew-aramaic/) · [Information retrieval & search (3)](https://md.research.elamur.ai/free/en/topics/information-retrieval/) · [Modern Hebrew (3)](https://md.research.elamur.ai/free/en/topics/modern-hebrew/) · [Word sense disambiguation (2)](https://md.research.elamur.ai/free/en/topics/word-sense-disambiguation/) · [Treebanks (2)](https://md.research.elamur.ai/free/en/topics/treebanks/) · [Summarization (2)](https://md.research.elamur.ai/free/en/topics/summarization/) · [Lexical semantics & word embeddings (2)](https://md.research.elamur.ai/free/en/topics/lexical-semantics/) · [Tokenization & segmentation (2)](https://md.research.elamur.ai/free/en/topics/tokenization/) · [Efficient models & compression (2)](https://md.research.elamur.ai/free/en/topics/efficient-models/) · [Speech act theory (1)](https://md.research.elamur.ai/free/en/topics/speech-act-theory/) · [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/) · [Sentiment & emotion (1)](https://md.research.elamur.ai/free/en/topics/sentiment-emotion/) · [Speech & spoken language (1)](https://md.research.elamur.ai/free/en/topics/speech/) · [Low-resource languages (1)](https://md.research.elamur.ai/free/en/topics/low-resource-languages/) · [Knowledge graphs & ontologies (1)](https://md.research.elamur.ai/free/en/topics/knowledge-graphs/) · [Interpretability (1)](https://md.research.elamur.ai/free/en/topics/interpretability/) · [Bias, fairness & safety (1)](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/) · [Grammatical error correction & learner language (1)](https://md.research.elamur.ai/free/en/topics/grammatical-error-correction/) · [French (1)](https://md.research.elamur.ai/free/en/topics/french/)

## Fields

[Computer Science (130)](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Arts and Humanities (128)](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Psychology (7)](https://md.research.elamur.ai/free/en/shelves/psychology/) · [Decision Sciences (4)](https://md.research.elamur.ai/free/en/shelves/decision-sciences/) · [Social Sciences (4)](https://md.research.elamur.ai/free/en/shelves/social-sciences/) · [Neuroscience (3)](https://md.research.elamur.ai/free/en/shelves/neuroscience/) · [Biochemistry, Genetics and Molecular Biology (2)](https://md.research.elamur.ai/free/en/shelves/biochemistry-genetics-and-molecular-biology/)

## Top authors

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

[🧑‍🔬**Yoav Goldberg**6 works here · 3,346 citations](https://md.research.elamur.ai/free/en/authors/yoav-goldberg/) · [🧑‍🔬**André F. T. Martins**5 works here · 676 citations](https://md.research.elamur.ai/free/en/authors/andre-f-t-martins/) · [🧑‍🔬**Michael Collins**4 works here · 5,299 citations](https://md.research.elamur.ai/free/en/authors/michael-collins/) · [🧑‍🔬**Percy Liang**4 works here · 3,636 citations](https://md.research.elamur.ai/free/en/authors/percy-liang/) · [🧑‍🔬**Tom Kwiatkowski**3 works here · 5,173 citations](https://md.research.elamur.ai/free/en/authors/tom-kwiatkowski/) · [🧑‍🔬**Kristina Toutanova**3 works here · 5,084 citations](https://md.research.elamur.ai/free/en/authors/kristina-toutanova/) · [🧑‍🔬**Graham Neubig**3 works here · 2,006 citations](https://md.research.elamur.ai/free/en/authors/graham-neubig/) · [🧑‍🔬**Ellie Pavlick**3 works here · 1,618 citations](https://md.research.elamur.ai/free/en/authors/ellie-pavlick/) · [🧑‍🔬**Chris Dyer**3 works here · 1,567 citations](https://md.research.elamur.ai/free/en/authors/chris-dyer/) · [🧑‍🔬**David Grangier**3 works here · 1,440 citations](https://md.research.elamur.ai/free/en/authors/david-grangier/) · [🧑‍🔬**Jacob Eisenstein**3 works here · 892 citations](https://md.research.elamur.ai/free/en/authors/jacob-eisenstein/) · [🧑‍🔬**Dan Garrette**3 works here · 880 citations](https://md.research.elamur.ai/free/en/authors/dan-garrette/)

## Top institutions

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

[🏢**Google** Mountain View · United States 18 works here](https://md.research.elamur.ai/free/en/companies/google/) · [🎓**Johns Hopkins University** Baltimore · United States 12 works here](https://md.research.elamur.ai/free/en/universities/johns-hopkins-university/) · [🎓**Stanford University** Stanford · United States 10 works here](https://md.research.elamur.ai/free/en/universities/stanford-university/) · [🎓**Bar-Ilan University** Ramat Gan · Israel 9 works here](https://md.research.elamur.ai/free/en/universities/bar-ilan-university/) · [🔬**Allen Institute for Artificial Intelligence** Seattle · United States 8 works here](https://md.research.elamur.ai/free/en/labs/allen-institute-for-artificial-intelligence/) · [🎓**Carnegie Mellon University** Pittsburgh · United States 7 works here](https://md.research.elamur.ai/free/en/universities/carnegie-mellon-university/) · [🎓**Massachusetts Institute of Technology** Cambridge · United States 6 works here](https://md.research.elamur.ai/free/en/universities/massachusetts-institute-of-technology/) · [🎓**University of Washington** Seattle · United States 5 works here](https://md.research.elamur.ai/free/en/universities/university-of-washington/) · [🎓**University of Cambridge** Cambridge · United Kingdom 5 works here](https://md.research.elamur.ai/free/en/universities/university-of-cambridge/) · [🏢**Meta** Menlo Park · United States 5 works here](https://md.research.elamur.ai/free/en/companies/meta/) · [🔬**Instituto de Telecomunicações** Lisbon · Portugal 5 works here](https://md.research.elamur.ai/free/en/labs/instituto-de-telecomunicacoes/) · [🎓**Instituto Superior Técnico** Lisbon · Portugal 5 works here](https://md.research.elamur.ai/free/en/universities/instituto-superior-tecnico/)

## Works in our library (132)

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

1. [**Natural Questions: A Benchmark for Question Answering Research**Tom Kwiatkowski, Jennimaria Palomaki, Olivia Redfield, et al.*2019 · 4,031 citations*](https://md.research.elamur.ai/free/en/papers/kwiatkowski-2019-natural-questions-benchmark-question-answering/)
2. [**SpanBERT: Improving Pre-training by Representing and Predicting Spans**Mandar Joshi, Danqi Chen, Yinhan Liu, et al.*2019 · 2,580 citations*](https://md.research.elamur.ai/free/en/papers/joshi-2019-spanbert-improving-pre-training-representing/)
3. [**Lost in the Middle: How Language Models Use Long Contexts**Nelson F. Liu, Kevin Lin, John Hewitt, et al.*2023 · 2,540 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-lost-middle-language-models-use/)
4. [**Named Entity Recognition with Bidirectional LSTM-CNNs**Jason P. C. Chiu, Eric Nichols*2015 · 2,276 citations*](https://md.research.elamur.ai/free/en/papers/chiu-2015-named-entity-recognition-bidirectional-lstm/)
5. [**Enriching Word Vectors with Subword Information**Piotr Bojanowski, Edouard Grave, Armand Joulin, et al.*2017 · 2,218 citations*](https://md.research.elamur.ai/free/en/papers/bojanowski-2017-enriching-word-vectors-subword-information/)
6. [**A Primer in BERTology: What We Know About How BERT Works**Anna Rogers, Olga Kovaleva, Anna Rumshisky*2020 · 2,127 citations*](https://md.research.elamur.ai/free/en/papers/rogers-2020-primer-bertology-what-we-know/)
7. [**CoQA: A Conversational Question Answering Challenge**Siva Reddy, Danqi Chen, Christopher D. Manning*2019 · 1,541 citations*](https://md.research.elamur.ai/free/en/papers/reddy-2019-coqa-conversational-question-answering-challenge/)
8. [**How Can We Know What Language Models Know?**Zhengbao Jiang, Frank F. Xu, Jun Araki, et al.*2020 · 1,493 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2020-how-can-we-know-what/)
9. [**Assessing the Ability of LSTMs to Learn Syntax-Sensitive Dependencies**Tal Linzen, Emmanuel Dupoux, Yoav Goldberg*2016 · 1,239 citations*](https://md.research.elamur.ai/free/en/papers/linzen-2016-assessing-ability-lstms-learn-syntax/)
10. [**ABCNN: Attention-Based Convolutional Neural Network for Modeling Sentence Pairs**Wenpeng Yin, Hinrich Schütze, Bing Xiang, et al.*2016 · 1,048 citations*](https://md.research.elamur.ai/free/en/papers/yin-2016-abcnn-attention-based-convolutional-neural/)
11. [**The NarrativeQA Reading Comprehension Challenge**Tomáš Kočiský, Jonathan Schwarz, Phil Blunsom, et al.*2018 · 1,026 citations*](https://md.research.elamur.ai/free/en/papers/kocisky-2018-narrativeqa-reading-comprehension-challenge/)
12. [**Optimizing Statistical Machine Translation for Text Simplification**Wei Xu, Courtney Napoles, Ellie Pavlick, et al.*2016 · 952 citations*](https://md.research.elamur.ai/free/en/papers/xu-2016-optimizing-statistical-machine-translation-text/)
13. [**Topic Modeling in Embedding Spaces**Adji B. Dieng, Francisco J. R. Ruiz, David M. Blei*2020 · 914 citations*](https://md.research.elamur.ai/free/en/papers/dieng-2020-topic-modeling-embedding-spaces/)
14. [**Grounded Compositional Semantics for Finding and Describing Images with Sentences**Richard Socher, Andrej Karpathy, Quoc V. Le, et al.*2014 · 909 citations*](https://md.research.elamur.ai/free/en/papers/socher-2014-grounded-compositional-semantics-finding-describing/)
15. [**Simple and Accurate Dependency Parsing Using Bidirectional LSTM Feature Representations**Eliyahu Kiperwasser, Yoav Goldberg*2016 · 903 citations*](https://md.research.elamur.ai/free/en/papers/kiperwasser-2016-simple-accurate-dependency-parsing-bidirectional/)
16. [**What BERT Is Not: Lessons from a New Suite of Psycholinguistic Diagnostics for Language Models**Allyson Ettinger*2020 · 843 citations*](https://md.research.elamur.ai/free/en/papers/ettinger-2020-what-bert-is-not-lessons/)
17. [**Analysis Methods in Neural Language Processing: A Survey**Yonatan Belinkov, James Glass*2019 · 735 citations*](https://md.research.elamur.ai/free/en/papers/belinkov-2019-analysis-methods-neural-language-processing/)
18. [**TyDi QA: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languages**Jonathan H. Clark, Eunsol Choi, Michael Collins, et al.*2020 · 691 citations*](https://md.research.elamur.ai/free/en/papers/clark-2020-tydi-qa-benchmark-information-seeking/)
19. [**Benchmarking Large Language Models for News Summarization**Tianyi Zhang, Faisal Ladhak, Esin Durmus, et al.*2024 · 663 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-benchmarking-large-language-models-news/)
20. [**Experts, Errors, and Context: A Large-Scale Study of Human Evaluation for Machine Translation**Markus Freitag, George Foster, David Grangier, et al.*2021 · 660 citations*](https://md.research.elamur.ai/free/en/papers/freitag-2021-experts-errors-context-large-scale/)
21. [**Efficient Content-Based Sparse Attention with Routing Transformers**Aurko Roy, Mohammad Saffar, Ashish Vaswani, et al.*2020 · 660 citations*](https://md.research.elamur.ai/free/en/papers/roy-2020-efficient-content-based-sparse-attention/)
22. [**Problems in Current Text Simplification Research: New Data Can Help**Wei Xu, Chris Callison-Burch, Courtney Napoles*2015 · 659 citations*](https://md.research.elamur.ai/free/en/papers/xu-2015-problems-current-text-simplification-research/)
23. [**A Survey on Automated Fact-Checking**Zhijiang Guo, Michael Schlichtkrull, Andreas Vlachos*2022 · 646 citations*](https://md.research.elamur.ai/free/en/papers/guo-2022-survey-automated-fact-checking/)
24. [**Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond**Mikel Artetxe, Holger Schwenk*2018 · 627 citations*](https://md.research.elamur.ai/free/en/papers/artetxe-2018-massively-multilingual-sentence-embeddings-zero/)
25. [**Weakly Supervised Learning of Semantic Parsers for Mapping Instructions to Actions**Yoav Artzi, Luke Zettlemoyer*2013 · 592 citations*](https://md.research.elamur.ai/free/en/papers/artzi-2013-weakly-supervised-learning-semantic-parsers/)

[See all 132 works →](https://md.research.elamur.ai/free/en/venues/tacl/works/)

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