The citation and collaboration graph of open research, drawn and linked to its sources.

The most-cited works in OpenAlex's Artificial Intelligence subfield, with every author and every citation edge that falls inside the set. Every page is precomputed and every graph is drawn here rather than in your browser, so there is no login, no per-month graph allowance and nothing to wait for.

3,000papers

6,906authors

13,915citation edges

61,645collaboration edges

4,521institutions

What this corpus is, exactly

The 3,000 most-cited works in OpenAlex's Artificial Intelligence subfield, every author on them, and every citation between two works that are both inside the set. That bound is committed to the repository as corpus.json, so “why is this paper here and not that one” has a diffable answer. 3,000 is where this starts, not the shape of the thing.

34% of author records here are marked low confidence, and 101 of 3,000 paper records contradict themselves. Author identity in every open bibliographic database is produced by an algorithm that splits one researcher across several records and merges several researchers into one. We do not fix that silently. Each author page states how confident it is and shows you the signals, and nothing is ever merged away. How that is judged.

Works by publication year (93 years)

Is each author record one person?

high 3,643 53%medium 890 13%low 2,373 34%

Does each paper record agree with itself?

complete 2,089 70%partial 810 27%suspect 101 3%

Most cited

Paper	Year	Cited	In corpus
Random Forests Leo Breiman	2001	131,109	45
Long Short-Term Memory Sepp Hochreiter, Jürgen Schmidhuber	1997	101,359	89
Fitting Linear Mixed-Effects Models Using lme4 Douglas M. Bates, Martin Mächler, Benjamin M. Bolker, Steve Walker	2015	88,296	0
Adam: A Method for Stochastic Optimization Diederik P. Kingma, Jimmy Ba	2014	84,698	56
Exploiting Generative AI to Scale up Intelligent Tutoring Systems	2023	79,071	29
Fuzzy sets L. A. Zadeh	1965	67,093	21
Scikit-learn: Machine Learning in Python Fabián Pedregosa, Gaël Varoquaux, Alexandre Gramfort, Vincent Michel and 12 more	2012	64,025	23
XGBoost	2016	52,304	10
[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)]	2015	50,396	52
Genetic algorithms in search, optimization, and machine learning	1989	49,344	56
Particle swarm optimization James Kennedy, R.C. Eberhart	2002	48,447	49
Fuzzy sets Lotfi A. Zadeh	1996	47,147	6
AI-Assisted Pipeline for Dynamic Generation of Trustworthy Health Supplement Content at Scale	2018	46,036	27
Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach Fred S. Guthery, Kenneth P. Burnham, David Anderson	2003	42,187	2
Support-vector networks Corinna Cortes, Vladimir Vapnik	1995	41,028	21
Matplotlib: A 2D Graphics Environment John D. Hunter	2007	40,822	11
SciPy 1.0: fundamental algorithms for scientific computing in Python	2020	39,642	2
The Nature of Statistical Learning Theory Vladimir Vapnik	1995	39,409	59
Adaptation in Natural and Artificial Systems John H. Holland	1992	35,569	67
Biostatistical Analysis William H. Baltosser, Jerrold H. Zar	1996	35,462	3
Dropout: a simple way to prevent neural networks from overfitting Nitish Srivastava, Geoffrey E. Hinton, Alex Krizhevsky, Ilya Sutskever and 1 more	2014	34,236	57
Glove: Global Vectors for Word Representation Jeffrey Pennington, Richard Socher, Christopher D. Manning	2014	34,067	40
ggplot2 Hadley Wickham	2016	33,962	2
Support-Vector Networks Corinna Cortes, Vladimir Vapnik	1995	33,914	36
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Jacob Devlin, Ming‐Wei Chang, Kenton Lee, Kristina Toutanova	2019	33,416	39
SMOTE: Synthetic Minority Over-sampling Technique Nitesh V. Chawla, Kevin W. Bowyer, Lawrence Hall, W. Philip Kegelmeyer	2002	32,402	25
Learning representations by back-propagating errors David E. Rumelhart, Geoffrey E. Hinton, Ronald J. Williams	1986	31,688	60
A New Approach to Linear Filtering and Prediction Problems R. E. Kalman	1960	31,488	11
The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data Aaron McKenna, Matthew G. Hanna, Eric Banks, Andrey Sivachenko and 7 more	2010	30,527	0
Greedy function approximation: A gradient boosting machine. Jerome H. Friedman	2001	30,137	19
Neural Networks: A Comprehensive Foundation Simon Haykin	1998	29,840	14
Reinforcement Learning: An Introduction Richard S. Sutton, Andy Barto	1998	27,409	13
Latent dirichlet allocation David M. Blei, Andrew Y. Ng, Michael I. Jordan	2003	27,078	31
Statistical Learning Theory Yuhai Wu, Vladimir Vapnik	1999	26,957	44
Random sample consensus Martin A. Fischler, Robert C. Bolles	1981	25,870	1
Reinforcement Learning: An Introduction	2005	25,758	27
Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation Kyunghyun Cho, Bart van Merriënboer, Çağlar Gülçehre, Dzmitry Bahdanau and 3 more	2014	25,048	27
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift Sergey Ioffe, Christian Szegedy	2015	24,404	32
C4.5: Programs for Machine Learning J. R. Quinlan	1992	23,704	48
A Survey on Transfer Learning Sinno Jialin Pan, Qiang Yang	2009	23,670	28

All 3,000 papers · All 6,906 authors