Łukasz Kaiser

29.0k total citations · 1 hit paper
30 papers, 771 citations indexed

About

Łukasz Kaiser is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computer Vision and Pattern Recognition. According to data from OpenAlex, Łukasz Kaiser has authored 30 papers receiving a total of 771 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Artificial Intelligence, 16 papers in Computational Theory and Mathematics and 6 papers in Computer Vision and Pattern Recognition. Recurrent topics in Łukasz Kaiser's work include Logic, Reasoning, and Knowledge (13 papers), Logic, programming, and type systems (7 papers) and Formal Methods in Verification (7 papers). Łukasz Kaiser is often cited by papers focused on Logic, Reasoning, and Knowledge (13 papers), Logic, programming, and type systems (7 papers) and Formal Methods in Verification (7 papers). Łukasz Kaiser collaborates with scholars based in France, Germany and United States. Łukasz Kaiser's co-authors include George Tucker, Anselm Levskaya, Nikita Kitaev, Geoffrey E. Hinton, Gabriel Pereyra, Jan Chorowski, Enrique Alfonseca, Oriol Vinyals, Katja Filippova and Martin Popel and has published in prestigious journals such as Nature Communications, Theoretical Computer Science and Lecture notes in computer science.

In The Last Decade

Łukasz Kaiser

28 papers receiving 724 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Regularizing Neural Networks by Penalizing Confident Output Distributions

2017 178 citations George Tucker, Łukasz Kaiser et al. arXiv (Cornell University) profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Łukasz Kaiser France	11	592	227	89	37	33	30	771
Francesco Locatello Germany	9	418 0.7×	168 0.7×	28 0.3×	33 0.9×	41 1.2×	27	698
Eunho Yang South Korea	15	405 0.7×	136 0.6×	44 0.5×	26 0.7×	127 3.8×	74	691
Murtadha Ahmed China	6	343 0.6×	115 0.5×	22 0.2×	52 1.4×	69 2.1×	17	643
Jinpeng Wang China	17	502 0.8×	457 2.0×	26 0.3×	33 0.9×	12 0.4×	58	810
Luca Rossi United Kingdom	13	284 0.5×	130 0.6×	50 0.6×	38 1.0×	28 0.8×	38	502
Alan Blair Australia	13	412 0.7×	84 0.4×	53 0.6×	18 0.5×	34 1.0×	48	583
Junbo Zhao China	6	305 0.5×	236 1.0×	22 0.2×	31 0.8×	34 1.0×	18	514
Eric Garcia United States	8	171 0.3×	213 0.9×	25 0.3×	52 1.4×	21 0.6×	13	442
Manuel Montes Mexico	11	475 0.8×	369 1.6×	25 0.3×	28 0.8×	27 0.8×	33	788
Carmen Peláez-Moreno Spain	12	286 0.5×	116 0.5×	118 1.3×	197 5.3×	61 1.8×	62	563

Countries citing papers authored by Łukasz Kaiser

Since Specialization

Citations

This map shows the geographic impact of Łukasz Kaiser's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Łukasz Kaiser with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Łukasz Kaiser more than expected).

Fields of papers citing papers by Łukasz Kaiser

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Łukasz Kaiser. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Łukasz Kaiser. The network helps show where Łukasz Kaiser may publish in the future.

Co-authorship network of co-authors of Łukasz Kaiser

This figure shows the co-authorship network connecting the top 25 collaborators of Łukasz Kaiser. A scholar is included among the top collaborators of Łukasz Kaiser based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Łukasz Kaiser. Łukasz Kaiser is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

1.

Kaiser, Łukasz, et al.. (2022). Hierarchical Transformers Are More Efficient Language Models. 1559–1571. 20 indexed citations

2.

Kozakowski, Piotr, et al.. (2022). Q-Value Weighted Regression: Reinforcement Learning with Limited Data. 2022 International Joint Conference on Neural Networks (IJCNN). 70. 1–8. 2 indexed citations

3.

Kaiser, Łukasz. (2021). Learning Games from Videos Guided by Descriptive Complexity. Proceedings of the AAAI Conference on Artificial Intelligence. 26(1). 963–969. 2 indexed citations

4.

Kaiser, Łukasz, Mohammad Babaeizadeh, Piotr Miłoś, et al.. (2020). Model Based Reinforcement Learning for Atari. International Conference on Learning Representations. 23 indexed citations

5.

Popel, Martin, Markéta Tomková, Jakub Tomek, et al.. (2020). Transforming machine translation: a deep learning system reaches news translation quality comparable to human professionals. Nature Communications. 11(1). 4381–4381. 163 indexed citations

6.

Kitaev, Nikita, Łukasz Kaiser, & Anselm Levskaya. (2020). Reformer: The Efficient Transformer. arXiv (Cornell University). 108 indexed citations

7.

Kaiser, Łukasz, Ofir Nachum, Aurko Roy, & Samy Bengio. (2017). Learning to Remember Rare Events. arXiv (Cornell University). 32 indexed citations

8.

Kaiser, Łukasz. (2012). Learning games from videos guided by descriptive complexity. National Conference on Artificial Intelligence. 963–969. 17 indexed citations

9.

Fischer, Diana & Łukasz Kaiser. (2012). Model Checking the Quantitative mu-Calculus on Linear Hybrid Systems. Logical Methods in Computer Science. Volume 8, Issue 3. 1 indexed citations

10.

Kaiser, Łukasz, et al.. (2012). Degrees of Lookahead in Regular Infinite Games. Logical Methods in Computer Science. Volume 8, Issue 3. 10 indexed citations

11.

Berwanger, Dietmar, et al.. (2012). Entanglement and the complexity of directed graphs. Theoretical Computer Science. 463. 2–25. 17 indexed citations

12.

Kaiser, Łukasz, et al.. (2012). A Counting Logic for Structure Transition Systems. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 380.

13.

Kaiser, Łukasz. (2011). Logic and Games on Automatic Structures: Playing with Quantifiers and Decompositions. Springer eBooks. 2 indexed citations

14.

Kaiser, Łukasz, et al.. (2011). First-order logic with counting for general game playing. National Conference on Artificial Intelligence. 791–796. 3 indexed citations

15.

Kaiser, Łukasz. (2011). Logic and Games on Automatic Structures. Lecture notes in computer science. 1 indexed citations

16.

Berwanger, Dietmar, et al.. (2011). Imperfect Recall and Counter Games. RWTH Publications (RWTH Aachen).

17.

Bárány, Vince, Łukasz Kaiser, & Alexander Rabinovich. (2010). Expressing Cardinality Quantifiers in Monadic Second-Order Logic over Trees. Fundamenta Informaticae. 100(1-4). 1–17. 9 indexed citations

18.

Fischer, Diana, Erich Grädel, & Łukasz Kaiser. (2009). Model Checking Games for the Quantitative μ-Calculus. Theory of Computing Systems. 47(3). 696–719. 9 indexed citations

19.

Grädel, Erich & Łukasz Kaiser. (2007). What kind of memory is needed to win infinitary Muller games?. RWTH Publications (RWTH Aachen). 2 indexed citations

20.

Kaiser, Łukasz. (2006). Game Quantification on Automatic Structures and Hierarchical Model Checking Games. RWTH Publications (RWTH Aachen). 6 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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