Sho Takase

703 total citations
31 papers, 316 citations indexed

About

Sho Takase is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Sho Takase has authored 31 papers receiving a total of 316 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Artificial Intelligence, 2 papers in Information Systems and 2 papers in Computer Vision and Pattern Recognition. Recurrent topics in Sho Takase's work include Topic Modeling (27 papers), Natural Language Processing Techniques (25 papers) and Advanced Text Analysis Techniques (7 papers). Sho Takase is often cited by papers focused on Topic Modeling (27 papers), Natural Language Processing Techniques (25 papers) and Advanced Text Analysis Techniques (7 papers). Sho Takase collaborates with scholars based in Japan and United States. Sho Takase's co-authors include Naoaki Okazaki, Jun Suzuki, Masaaki Nagata, Tsutomu Hirao, Shun Kiyono, Kentaro Inui, Atsushi Keyaki, Naoya Inoue, Hidetaka Kamigaito and Masahiro Kaneko and has published in prestigious journals such as Engineering Applications of Artificial Intelligence, Language Resources and Evaluation and ACM Transactions on Asian and Low-Resource Language Information Processing.

In The Last Decade

Sho Takase

27 papers receiving 295 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sho Takase Japan 10 286 52 29 12 8 31 316
Honglun Zhang China 7 209 0.7× 47 0.9× 28 1.0× 7 0.6× 4 0.5× 11 242
Guanghui Qin United States 6 223 0.8× 63 1.2× 28 1.0× 8 0.7× 5 0.6× 10 254
Eunah Cho Germany 13 441 1.5× 91 1.8× 26 0.9× 14 1.2× 3 0.4× 41 463
Shuailiang Zhang China 3 242 0.8× 79 1.5× 20 0.7× 11 0.9× 3 0.4× 3 264
Zhenghao Liu China 10 208 0.7× 40 0.8× 62 2.1× 10 0.8× 7 0.9× 31 251
Or Honovich Israel 7 199 0.7× 40 0.8× 29 1.0× 6 0.5× 3 0.4× 10 221
Avi Caciularu Israel 9 206 0.7× 57 1.1× 58 2.0× 13 1.1× 8 1.0× 29 255
Amir Kantor Israel 5 181 0.6× 40 0.8× 48 1.7× 12 1.0× 4 0.5× 14 237
Kenton Murray United States 7 115 0.4× 34 0.7× 37 1.3× 7 0.6× 3 0.4× 19 139

Countries citing papers authored by Sho Takase

Since Specialization
Citations

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

Fields of papers citing papers by Sho Takase

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sho Takase

This figure shows the co-authorship network connecting the top 25 collaborators of Sho Takase. A scholar is included among the top collaborators of Sho Takase 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 Sho Takase. Sho Takase 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.
Takase, Sho & Shun Kiyono. (2023). Lessons on Parameter Sharing across Layers in Transformers. 78–90. 15 indexed citations
2.
Takase, Sho, et al.. (2023). Nearest Neighbor Non-autoregressive Text Generation. Journal of Information Processing. 31(0). 344–352. 4 indexed citations
3.
4.
Takase, Sho, et al.. (2023). ExtraPhrase: Efficient Data Augmentation for Abstractive Summarization. Journal of Natural Language Processing. 30(2). 489–506.
5.
Takase, Sho, Shun Kiyono, Sosuke Kobayashi, & Jun Suzuki. (2023). B2T Connection: Serving Stability and Performance in Deep Transformers. 3078–3095. 4 indexed citations
6.
Takase, Sho, et al.. (2022). Single Model Ensemble for Subword Regularized Models in Low-Resource Machine Translation. Findings of the Association for Computational Linguistics: ACL 2022. 2536–2541.
7.
Takase, Sho. (2021). Report on the 16th Symposiums of Young Researcher Association for NLP Studies. Journal of Natural Language Processing. 28(4). 1307–1311. 3 indexed citations
8.
Takase, Sho, et al.. (2021). Recurrent Neural Hidden Markov Model for High-order Transition. ACM Transactions on Asian and Low-Resource Language Information Processing. 21(2). 1–15. 3 indexed citations
9.
Takase, Sho & Shun Kiyono. (2021). Rethinking Perturbations in Encoder-Decoders for Fast Training. 5767–5780. 24 indexed citations
10.
Takase, Sho, et al.. (2021). Joint Optimization of Tokenization and Downstream Model. 244–255. 7 indexed citations
11.
Takase, Sho, et al.. (2020). Evaluation Dataset for Zero Pronoun in Japanese to English Translation. Language Resources and Evaluation. 3630–3634. 4 indexed citations
12.
Takase, Sho, et al.. (2020). Improving Truthfulness of Headline Generation. 1335–1346. 22 indexed citations
13.
Takase, Sho, et al.. (2019). Neural Question Generation using Interrogative Phrases. 106–111. 2 indexed citations
14.
Kiyono, Shun, Sho Takase, Jun Suzuki, et al.. (2018). Unsupervised Token-wise Alignment to Improve Interpretation of Encoder-Decoder Models. 74–81. 4 indexed citations
15.
Suzuki, Jun, Sho Takase, Hidetaka Kamigaito, Makoto Morishita, & Masaaki Nagata. (2018). An Empirical Study of Building a Strong Baseline for Constituency Parsing. 612–618. 11 indexed citations
16.
Kiyono, Shun, Sho Takase, Jun Suzuki, et al.. (2018). Reducing Odd Generation from Neural Headline Generation. Tokyo Tech Research Repository (Tokyo Institute of Technology). 3 indexed citations
17.
Takase, Sho, Jun Suzuki, & Masaaki Nagata. (2018). Direct Output Connection for a High-Rank Language Model. 4599–4609. 17 indexed citations
18.
Takase, Sho, Naoaki Okazaki, & Kentaro Inui. (2016). Composing Distributed Representations of Relational Patterns. 2276–2286. 5 indexed citations
19.
Takase, Sho, Naoaki Okazaki, & Kentaro Inui. (2015). Fast and Large-scale Unsupervised Relation Extraction. Waseda University Repository (Waseda University). 96–105. 6 indexed citations
20.
Takase, Sho, et al.. (2013). Detecting Chronic Critics Based on Sentiment Polarity and User’s Behavior in Social Media. Meeting of the Association for Computational Linguistics. 110–116. 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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