Kazuma Hashimoto

2.3k total citations
32 papers, 667 citations indexed

About

Kazuma Hashimoto is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, Kazuma Hashimoto has authored 32 papers receiving a total of 667 indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Artificial Intelligence, 13 papers in Computer Vision and Pattern Recognition and 3 papers in Molecular Biology. Recurrent topics in Kazuma Hashimoto's work include Topic Modeling (28 papers), Natural Language Processing Techniques (24 papers) and Multimodal Machine Learning Applications (13 papers). Kazuma Hashimoto is often cited by papers focused on Topic Modeling (28 papers), Natural Language Processing Techniques (24 papers) and Multimodal Machine Learning Applications (13 papers). Kazuma Hashimoto collaborates with scholars based in Japan, United States and United Kingdom. Kazuma Hashimoto's co-authors include Yoshimasa Tsuruoka, Akiko Eriguchi, Makoto Miwa, Caiming Xiong, Yingbo Zhou, Semih Yavuz, Sophia Ananiadou, Georgios Kontonatsios, Richard Socher and Takashi Chikayama and has published in prestigious journals such as Future Generation Computer Systems, Applied Sciences and Journal of Biomedical Informatics.

In The Last Decade

Kazuma Hashimoto

30 papers receiving 614 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kazuma Hashimoto Japan 13 610 147 84 68 21 32 667
Diego Marcheggiani Italy 8 601 1.0× 106 0.7× 75 0.9× 78 1.1× 33 1.6× 14 671
Weiran Xu China 12 504 0.8× 85 0.6× 104 1.2× 32 0.5× 30 1.4× 78 593
Yuning Mao United States 13 422 0.7× 113 0.8× 65 0.8× 39 0.6× 21 1.0× 25 477
Arvind Neelakantan United States 8 607 1.0× 68 0.5× 44 0.5× 33 0.5× 57 2.7× 11 645
Gregory Druck United States 9 450 0.7× 91 0.6× 70 0.8× 32 0.5× 9 0.4× 15 514
Johannes Leveling Ireland 8 544 0.9× 125 0.9× 136 1.6× 84 1.2× 18 0.9× 69 645
Yajuan Lyu China 16 865 1.4× 226 1.5× 124 1.5× 64 0.9× 71 3.4× 32 917
Giannis Bekoulis Belgium 8 440 0.7× 43 0.3× 79 0.9× 81 1.2× 58 2.8× 14 504
Arzoo Katiyar United States 7 705 1.2× 77 0.5× 77 0.9× 54 0.8× 98 4.7× 11 742

Countries citing papers authored by Kazuma Hashimoto

Since Specialization
Citations

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

Fields of papers citing papers by Kazuma Hashimoto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kazuma Hashimoto

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

All Works

20 of 20 papers shown
1.
Raman, Karthik, et al.. (2022). Transforming Sequence Tagging Into A Seq2Seq Task. 11856–11874. 8 indexed citations
2.
Ye, Xi, Semih Yavuz, Kazuma Hashimoto, Yingbo Zhou, & Caiming Xiong. (2022). RNG-KBQA: Generation Augmented Iterative Ranking for Knowledge Base Question Answering. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 6032–6043. 41 indexed citations
3.
Hashimoto, Kazuma, et al.. (2022). [CASPI] Causal-aware Safe Policy Improvement for Task-oriented Dialogue. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 92–102. 4 indexed citations
4.
5.
Zhang, Haopeng, Semih Yavuz, Wojciech Kryściński, Kazuma Hashimoto, & Yingbo Zhou. (2022). Improving the Faithfulness of Abstractive Summarization via Entity Coverage Control. 528–535. 19 indexed citations
6.
Wan, Yao, Jianguo Zhang, Yulei Sui, et al.. (2022). NaturalCC. 149–153. 8 indexed citations
7.
Yavuz, Semih, Kazuma Hashimoto, Yingbo Zhou, Nitish Shirish Keskar, & Caiming Xiong. (2022). Modeling Multi-hop Question Answering as Single Sequence Prediction. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 974–990. 12 indexed citations
8.
Niu, Tong, Kazuma Hashimoto, Yingbo Zhou, & Caiming Xiong. (2022). OneAligner: Zero-shot Cross-lingual Transfer with One Rich-Resource Language Pair for Low-Resource Sentence Retrieval. Findings of the Association for Computational Linguistics: ACL 2022. 2869–2882. 3 indexed citations
9.
10.
Liu, Ye, Kazuma Hashimoto, Yingbo Zhou, et al.. (2021). Dense Hierarchical Retrieval for Open-domain Question Answering. 188–200. 12 indexed citations
11.
12.
Esteva, Andre, et al.. (2021). COVID-19 information retrieval with deep-learning based semantic search, question answering, and abstractive summarization. npj Digital Medicine. 4(1). 68–68. 61 indexed citations
13.
Yavuz, Semih, Kazuma Hashimoto, Wenhao Liu, et al.. (2020). Simple Data Augmentation with the Mask Token Improves Domain Adaptation for Dialog Act Tagging. 5083–5089. 2 indexed citations
14.
Hashimoto, Kazuma, et al.. (2019). A High-Quality Multilingual Dataset for Structured Documentation Translation. 116–127. 6 indexed citations
15.
Hashimoto, Kazuma, Akiko Eriguchi, Haixia Wang, et al.. (2017). Cache Friendly Parallelization of Neural Encoder-Decoder Models Without Padding on Multi-core Architecture. 2. 437–440. 3 indexed citations
16.
Eriguchi, Akiko, Kazuma Hashimoto, & Yoshimasa Tsuruoka. (2016). Character-based Decoding in Tree-to-Sequence Attention-based Neural Machine Translation. International Conference on Computational Linguistics. 175–183. 8 indexed citations
17.
Hashimoto, Kazuma, Akiko Eriguchi, & Yoshimasa Tsuruoka. (2016). Domain Adaptation and Attention-Based Unknown Word Replacement in Chinese-to-Japanese Neural Machine Translation.. International Conference on Computational Linguistics. 75–83. 4 indexed citations
18.
Eriguchi, Akiko, Kazuma Hashimoto, & Yoshimasa Tsuruoka. (2016). Tree-to-Sequence Attentional Neural Machine Translation. 823–833. 160 indexed citations
19.
Hashimoto, Kazuma, Georgios Kontonatsios, Makoto Miwa, & Sophia Ananiadou. (2016). Topic detection using paragraph vectors to support active learning in systematic reviews. Journal of Biomedical Informatics. 62. 59–65. 66 indexed citations
20.
Hashimoto, Kazuma, Makoto Miwa, Yoshimasa Tsuruoka, & Takashi Chikayama. (2013). Simple Customization of Recursive Neural Networks for Semantic Relation Classification. 1372–1376. 61 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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