Yusuke Oda

846 total citations
11 papers, 267 citations indexed

About

Yusuke Oda is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, Yusuke Oda has authored 11 papers receiving a total of 267 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 3 papers in Computer Vision and Pattern Recognition and 2 papers in Molecular Biology. Recurrent topics in Yusuke Oda's work include Natural Language Processing Techniques (11 papers), Topic Modeling (11 papers) and Multimodal Machine Learning Applications (3 papers). Yusuke Oda is often cited by papers focused on Natural Language Processing Techniques (11 papers), Topic Modeling (11 papers) and Multimodal Machine Learning Applications (3 papers). Yusuke Oda collaborates with scholars based in Japan, United States and United Kingdom. Yusuke Oda's co-authors include Graham Neubig, Satoshi Nakamura, Sakriani Sakti, Tomoki Toda, Hideaki Hata, Katsuhito Sudoh, Koichiro Yoshino, Makoto Morishita, Andrew Finch and Hajime Tsukada and has published in prestigious journals such as NAIST Digital Library (Nara Institute of Science and Technology), International Conference on Computational Linguistics and IWSLT.

In The Last Decade

Yusuke Oda

10 papers receiving 237 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Yusuke Oda Japan	7	215	108	49	49	26	11	267
Maxim Rabinovich United States	5	158 0.7×	89 0.8×	39 0.8×	34 0.7×	22 0.8×	6	210
Jaime Font Spain	10	152 0.7×	215 2.0×	20 0.4×	104 2.1×	15 0.6×	34	251
Daoguang Zan China	6	117 0.5×	95 0.9×	10 0.2×	66 1.3×	19 0.7×	11	202
Krzysztof Stencel Poland	7	68 0.3×	94 0.9×	11 0.2×	35 0.7×	27 1.0×	42	150
Adrian Lienhard Switzerland	9	94 0.4×	119 1.1×	13 0.3×	50 1.0×	16 0.6×	18	171
Dawn Drain United Kingdom	3	150 0.7×	218 2.0×	15 0.3×	99 2.0×	82 3.2×	3	275
Avi Caciularu Israel	9	206 1.0×	58 0.5×	57 1.2×	7 0.1×	12 0.5×	29	255
Frank Steinbrückner Germany	4	92 0.4×	257 2.4×	58 1.2×	143 2.9×	31 1.2×	6	285
Scott Yih United States	9	272 1.3×	48 0.4×	90 1.8×	4 0.1×	10 0.4×	19	303
Dragan Bojić Serbia	8	61 0.3×	96 0.9×	9 0.2×	45 0.9×	8 0.3×	28	158

Countries citing papers authored by Yusuke Oda

Since Specialization

Citations

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

Fields of papers citing papers by Yusuke Oda

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yusuke Oda

This figure shows the co-authorship network connecting the top 25 collaborators of Yusuke Oda. A scholar is included among the top collaborators of Yusuke Oda 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 Yusuke Oda. Yusuke Oda 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:

11 of 11 papers shown

1.

Birch, Alexandra, Andrew Finch, Minh-Thang Luong, Graham Neubig, & Yusuke Oda. (2018). Findings of the Second Workshop on Neural Machine Translation and Generation. 1–10. 4 indexed citations

2.

Oda, Yusuke, Philip Arthur, Graham Neubig, Koichiro Yoshino, & Satoshi Nakamura. (2017). Neural Machine Translation via Binary Code Prediction. 850–860. 7 indexed citations

3.

Morishita, Makoto, Yusuke Oda, Graham Neubig, et al.. (2017). An Empirical Study of Mini-Batch Creation Strategies for Neural Machine Translation. 61–68. 14 indexed citations

4.

Oda, Yusuke, Katsuhito Sudoh, Satoshi Nakamura, Masao Utiyama, & Eiichiro Sumita. (2017). A Simple and Strong Baseline: NAIST-NICT Neural Machine Translation System for WAT2017 English-Japanese Translation Task. 135–139. 2 indexed citations

5.

Oda, Yusuke, Taku Kudo, Tetsuji Nakagawa, & Taro Watanabe. (2016). Phrase-based Machine Translation using Multiple Preordering Candidates. International Conference on Computational Linguistics. 1419–1428.

6.

Oda, Yusuke, Graham Neubig, Sakriani Sakti, Tomoki Toda, & Satoshi Nakamura. (2015). Syntax-based Simultaneous Translation through Prediction of Unseen Syntactic Constituents. 198–207. 19 indexed citations

7.

Oda, Yusuke, Graham Neubig, Hideaki Hata, et al.. (2015). Pseudogen: A Tool to Automatically Generate Pseudo-Code from Source Code. 824–829. 7 indexed citations

8.

Oda, Yusuke, Graham Neubig, Sakriani Sakti, Tomoki Toda, & Satoshi Nakamura. (2015). Ckylark: A More Robust PCFG-LA Parser. 41–45. 10 indexed citations

9.

Oda, Yusuke, Graham Neubig, Hideaki Hata, et al.. (2015). Learning to Generate Pseudo-Code from Source Code Using Statistical Machine Translation. NAIST Digital Library (Nara Institute of Science and Technology). 574–584. 151 indexed citations

10.

Neubig, Graham, Katsuhito Sudoh, Yusuke Oda, et al.. (2014). The NAIST-NTT TED talk treebank.. IWSLT. 5 indexed citations

11.

Oda, Yusuke, Graham Neubig, Sakriani Sakti, Tomoki Toda, & Satoshi Nakamura. (2014). Optimizing Segmentation Strategies for Simultaneous Speech Translation. 551–556. 48 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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