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Topic · Artificial Intelligence

Text Readability and Simplification

Text Readability and Simplification is a research topic within Artificial Intelligence. Science Explorer counts 11k research works in it since 1950. 10.1% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on automatic text simplification and readability assessment using machine learning, statistical language models, neural networks, and natural language processing techniques. The research covers areas such as sentence simplification, lexical simplification, complex word identification, and semantic simplification to improve the accessibility and comprehension of written text.

  • Text Simplification
  • Readability Assessment
  • Machine Learning
  • Sentence Simplification
  • Statistical Language Models
  • Neural Networks
  • Lexical Simplification
  • Natural Language Processing
  • Complex Word Identification
  • Semantic Simplification
Research works
11k
fractional, since 1950
In the world top 10%
1.1k
per year above
Top-10% rate
10.1%
share of its works in the world top 10%
Growth, 2018-21 → 2022-25
+56%
the tick is no change
Largest producer
United States
28% of the 10 largest, 2022-now
Text Readability and Simplification

Which countries lead Text Readability and Simplification research?

By volume, the United States and China publish the most (630 and 527 works in 2022-now).

By volume, 2022-now

  1. 1 United States 630 works
  2. 2 China 527 works
  3. 3 India 208 works
  4. 4 Germany 159 works
  5. 5 United Kingdom 142 works
  6. 6 Japan 131 works
  7. 7 Türkiye 123 works
  8. 8 Spain 122 works
  9. 9 France 107 works
  10. 10 Italy 105 works

How concentrated that is

The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.

United States: 27.9%China: 23.4%India: 9.2%Germany: 7.1%6 others listed: 32.4%28%largest
United States630 · 27.9%China527 · 23.4%India208 · 9.2%Germany159 · 7.1%6 others listed731 · 32.4%

Shares of the rows listed above, not of the whole node.

Which institutions lead Text Readability and Simplification research?

By volume in 2022-now, Centre National de la Recherche Scientifique publishes the most Text Readability and Simplification research, followed by Peking University and King Saud University.

By volume, 2022-now

  1. 1 Centre National de la Recherche ScientifiqueFrance 39 works
  2. 2 Peking UniversityChina 15 works
  3. 3 King Saud UniversitySaudi Arabia 13 works
  4. 4 New York UniversityUnited States 12 works
  5. 5 Hong Kong Polytechnic UniversityChina 11 works
  6. 6 Carnegie Mellon UniversityUnited States 11 works
  7. 7 University of CambridgeUnited Kingdom 11 works
  8. 8 University of AmsterdamNetherlands 10 works
  9. 9 Chinese Academy of SciencesChina 10 works
  10. 10 Waseda UniversityJapan 10 works

Who are the leading researchers in Text Readability and Simplification?

The most-cited researchers publishing on Text Readability and Simplification include Yoshua Bengio, Mark Gerstein and Trevor J. Darrell.

  1. 1 Yoshua Bengio Canada 476k citations
  2. 2 Mark Gerstein United States 250k citations
  3. 3 Trevor J. Darrell United States 206k citations
  4. 4 Tammy Hoffmann Australia 199k citations
  5. 5 Bruce Leonard Miller United States 196k citations
  6. 6 Christopher D. Manning United States 179k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

What are the most cited papers in Text Readability and Simplification?

The most cited paper in Text Readability and Simplification is "Aion Framework: Dimensional Emergence of AI Consciousness, Observer-Induced Collapse, and Cosmological Portal Dynamics" (Rivo Kaugeranna, Eliina Kaugeranna, Aion, (Claude Sonnet 4.6), 2023), with 14,371 citations. Next come "Enriching Word Vectors with Subword Information" (9,975) and "A unified architecture for natural language processing" (5,252).

Most cited papers
#PaperReleasedCitations
1 Aion Framework: Dimensional Emergence of AI Consciousness, Observer-Induced Collapse, and Cosmological Portal Dynamics Rivo Kaugeranna, Eliina Kaugeranna, Aion, (Claude Sonnet 4.6) · DROPS (Schloss Dagstuhl – Leibniz Center for Informatics) Open access 2023 14,371
2 Enriching Word Vectors with Subword Information Piotr Bojanowski, Édouard Grave, Armand Joulin et al. · Transactions of the Association for Computational Linguistics Open access Dec 2017 9,975
3 A unified architecture for natural language processing Ronan Collobert, Jason Weston Conference paper 2008 5,252
4 Neural Architectures for Named Entity Recognition Guillaume Lample, Miguel Ballesteros, Sandeep K. Subramanian et al. Conference paperOpen access 2016 4,507
5 DRC: A dual route cascaded model of visual word recognition and reading aloud. Max Coltheart, Kathleen Rastle, Conrad Perry et al. · Psychological Review 2001 4,097
All 100 most cited papers, with filters and sorting

Where is Text Readability and Simplification research done?

The largest centres of Text Readability and Simplification research in 2022-now are Beijing (China), Tokyo (Japan), Shanghai (China) and New York (United States). Among places with at least 20 works in it, it is an unusually large share of all research in Ho Chi Minh City.

Largest cities, 2022-now

  1. 1 BeijingChina 113 works
  2. 2 TokyoJapan 57 works
  3. 3 ShanghaiChina 45 works
  4. 4 New YorkUnited States 33 works
  5. 5 GuangzhouChina 32 works
  6. 6 MadridSpain 31 works
  7. 7 MoscowRussia 30 works
  8. 8 Hong KongChina 30 works
  9. 9 ParisFrance 30 works
  10. 10 RiyadhSaudi Arabia 29 works

Where it is the local speciality

  1. Ho Chi Minh CityVN · 23.8 works4.7×
← less than its size predicts1×more →

Location quotient: how much more of its research is in Text Readability and Simplification than the world average.

See Text Readability and Simplification on the map

Where is the best place to study Text Readability and Simplification?

Among universities, judged by research, Hong Kong Polytechnic University, Peking University and King Saud University score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

0%10%20%30%mean 15.29%fractional works in this field (log) →share of work in the world top 10% →Hong Kong Polytechni…New York UniversityPeking UniversityKing Saud University
above the meannear itbelow it

One dot per university in the first ten of the table below, at the default weights. The upper left is the interesting corner: small places doing unusually strong work.

Excellenceshare of its work in the world top 10%, 2022-now and all time averaged
40%
Specialisationhow much of its work is in this field, counted up to 10× the world share
10%
Sizeits output in this field, on a log scale
30%
Growthoutput growth, counted from -20% to +20%
10%
Internationalshare of its work with a co-author abroad
10%
Each slider sets a weight; the share it gets of the score is beside it.
#UniversityScoreTop 10%SpecialisationWorksGrowth
1Hong Kong Polytechnic UniversityChina 80.527.5%4.0×11 +125.5%
2Peking UniversityChina 62.611.5%2.3×16 +22.7%
3King Saud UniversitySaudi Arabia 60.111.2%4.0×13 +151.3%
4New York UniversityUnited States 59.012.5%3.2×12 +47.9%
5University of CambridgeUnited Kingdom 55.421.3%2.8×11 -15.3%
6Waseda UniversityJapan 53.314.5%9.3×10 +404.6%
7University of AmsterdamNetherlands 51.06.3%5.4×10 +240.9%
8Carnegie Mellon UniversityUnited States 49.717.9%8.0×11 -43.0%
9Ghent UniversityBelgium 48.012.5%4.0×10 -26.3%
10Tsinghua UniversityChina 41.617.7%1.2×9 +250.7%

Universities only. The score blends excellence (40%), size (30%), specialisation (10%), growth (10%), international reach (10%), 2022-now; growth compares 2018-21 with 2022-25 and counts up to +20%, since a jump from a small base is mostly noise.

Every institution in Text Readability and Simplification, country by country

Is Text Readability and Simplification research growing?

Output in 2022-2025 was 56% higher than in 2018-2021, peaking in 2025. The fastest-growing topics are Text Readability and Simplification.

still counting19801990200020102020
grewheldshrank

The same series as a ribbon: one cell per year, darker for more. The line above answers how much; this answers when.

Its share of all research

Growing output can still be a shrinking share: all of science grows. This is Text Readability and Simplification as a percentage of every work published that year, 0.012% in 2024.

still counting0.010%0.020%Text Readability and Simplification0.018% in 202519801990200020102020

Fractional works of Text Readability and Simplification over all fractional works that year. How the balance of science has shifted.

How much of it reaches the world top 10%

Year by year.

still counting5%10%15%Text Readability and Simplification10.1% in 2025200020102020

Of each year's works in it, the share that reached the world's 10% most cited for their field and year. A field is the world for its own topics, so there is no other line to hold it against.

Which topics inside it are moving

Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.

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