Akari Asai

71 total papers · 2.3k total citations
25 papers, 797 citations indexed

About

Akari Asai is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Communication. According to data from OpenAlex, Akari Asai has authored 25 papers receiving a total of 797 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Artificial Intelligence, 14 papers in Computer Vision and Pattern Recognition and 4 papers in Communication. Recurrent topics in Akari Asai's work include Topic Modeling (18 papers), Natural Language Processing Techniques (15 papers) and Multimodal Machine Learning Applications (11 papers). Akari Asai is often cited by papers focused on Topic Modeling (18 papers), Natural Language Processing Techniques (15 papers) and Multimodal Machine Learning Applications (11 papers). Akari Asai collaborates with scholars based in United States, Japan and United Kingdom. Akari Asai's co-authors include Ikuya Yamada, Hideaki Takeda, Hiroyuki Shindo, Yūji Matsumoto, Hannaneh Hajishirzi, Eunsol Choi, Yoshiyasu Takefuji, Raj Das, Daniel Khashabi and Victor W. Zhong and has published in prestigious journals such as arXiv (Cornell University), Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies and International Conference on Learning Representations.

In The Last Decade

Akari Asai

21 papers receiving 755 citations

Hit Papers

LUKE: Deep Contextualized... 2020 2026 2022 2024 2020 2023 100 200 300

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Akari Asai 705 177 112 70 45 25 797
Bharat Ram Ambati 674 1.0× 110 0.6× 101 0.9× 31 0.4× 66 1.5× 22 806
Sam Wiseman 853 1.2× 270 1.5× 79 0.7× 36 0.5× 34 0.8× 21 925
Tejaswini Deoskar 578 0.8× 105 0.6× 94 0.8× 29 0.4× 68 1.5× 17 714
Varun Manjunatha 675 1.0× 240 1.4× 80 0.7× 43 0.6× 28 0.6× 18 840
Wei-Yun Ma 662 0.9× 72 0.4× 125 1.1× 76 1.1× 56 1.2× 42 782
Ian Tenney 783 1.1× 186 1.1× 102 0.9× 26 0.4× 37 0.8× 13 937
Marina Danilevsky 543 0.8× 76 0.4× 143 1.3× 39 0.6× 38 0.8× 37 717
Samuel Cahyawijaya 604 0.9× 77 0.4× 121 1.1× 43 0.6× 21 0.5× 35 805
Mark E Neumann 690 1.0× 142 0.8× 69 0.6× 41 0.6× 107 2.4× 29 846
Nanda Kambhatla 792 1.1× 76 0.4× 151 1.3× 62 0.9× 99 2.2× 25 901

Countries citing papers authored by Akari Asai

Since Specialization
Citations

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

Fields of papers citing papers by Akari Asai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Akari Asai

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

All Works

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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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