János Kramár

841 total citations
8 papers, 152 citations indexed

About

János Kramár is a scholar working on Artificial Intelligence, Management Science and Operations Research and Computer Networks and Communications. According to data from OpenAlex, János Kramár has authored 8 papers receiving a total of 152 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Artificial Intelligence, 2 papers in Management Science and Operations Research and 1 paper in Computer Networks and Communications. Recurrent topics in János Kramár's work include Auction Theory and Applications (2 papers), Reinforcement Learning in Robotics (1 paper) and Multi-Agent Systems and Negotiation (1 paper). János Kramár is often cited by papers focused on Auction Theory and Applications (2 papers), Reinforcement Learning in Robotics (1 paper) and Multi-Agent Systems and Negotiation (1 paper). János Kramár collaborates with scholars based in United Kingdom, Canada and United States. János Kramár's co-authors include Ziyu Wang, Yuke Zhu, Raia Hadsell, Josh Merel, Serkan Cabi, Tom Erez, Saran Tunyasuvunakool, Nicolas Heess, Andrei A. Rusu and Nando de Freitas and has published in prestigious journals such as Nature Communications, Scientific Reports and Meeting of the Association for Computational Linguistics.

In The Last Decade

János Kramár

7 papers receiving 148 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
János Kramár United Kingdom	4	90	80	43	32	12	8	152
Patrick MacAlpine United States	8	88 1.0×	41 0.5×	52 1.2×	73 2.3×	10 0.8×	17	176
Alex Irpan United States	4	101 1.1×	95 1.2×	61 1.4×	42 1.3×	8 0.7×	5	170
Mohi Khansari United States	4	84 0.9×	77 1.0×	80 1.9×	23 0.7×	5 0.4×	9	154
Riad Akrour Germany	8	93 1.0×	56 0.7×	28 0.7×	12 0.4×	3 0.3×	13	139
Deirdre Quillen United States	3	118 1.3×	72 0.9×	46 1.1×	35 1.1×	5 0.4×	3	173
Jiafei Duan United States	5	77 0.9×	35 0.4×	86 2.0×	11 0.3×	8 0.7×	7	205
Samson Yu Singapore	4	69 0.8×	32 0.4×	83 1.9×	11 0.3×	8 0.7×	4	192
Abbas Abdolmaleki Portugal	9	112 1.2×	46 0.6×	29 0.7×	38 1.2×	10 0.8×	29	163
Florian Golemo Canada	4	54 0.6×	38 0.5×	53 1.2×	12 0.4×	7 0.6×	7	130
Simon Stepputtis United States	8	78 0.9×	112 1.4×	60 1.4×	30 0.9×	4 0.3×	20	213

Countries citing papers authored by János Kramár

Since Specialization

Citations

This map shows the geographic impact of János Kramár'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 János Kramár with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites János Kramár more than expected).

Fields of papers citing papers by János Kramár

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by János Kramár. 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 János Kramár. The network helps show where János Kramár may publish in the future.

Co-authorship network of co-authors of János Kramár

This figure shows the co-authorship network connecting the top 25 collaborators of János Kramár. A scholar is included among the top collaborators of János Kramár 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 János Kramár. János Kramár is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

8 of 8 papers shown

1.

Smith, Lewis, et al.. (2024). Gemma Scope: Open Sparse Autoencoders Everywhere All At Once on Gemma 2. 278–300. 4 indexed citations

2.

Goodman, Noah D., et al.. (2024). On scalable oversight with weak LLMs judging strong LLMs. 75229–75276.

3.

Anthony, T, et al.. (2022). Designing all-pay auctions using deep learning and multi-agent simulation. Scientific Reports. 12(1). 16937–16937. 1 indexed citations

4.

Kramár, János, Tom Eccles, Andrea Tacchetti, et al.. (2022). Negotiation and honesty in artificial intelligence methods for the board game of Diplomacy. Nature Communications. 13(1). 7214–7214. 11 indexed citations

5.

Bachrach, Yoram, Marta Garnelo, János Kramár, et al.. (2021). A Neural Network Auction For Group Decision Making Over a Continuous Space. 4976–4979. 2 indexed citations

6.

Tacchetti, Andrea, Hui Song, Pedro A. M. Mediano, et al.. (2018). Relational Forward Models for Multi-Agent Learning. UCL Discovery (University College London). 7 indexed citations

7.

Zhu, Yuke, Ziyu Wang, Josh Merel, et al.. (2018). Reinforcement and Imitation Learning for Diverse Visuomotor Skills. 126 indexed citations

8.

Krakovna, Victoria, et al.. (2010). A Generalized-Zero-Preserving Method for Compact Encoding of Concept Lattices. Meeting of the Association for Computational Linguistics. 1512–1521. 1 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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