Ryuichiro Higashinaka

1.9k total citations
124 papers, 1.0k citations indexed

About

Ryuichiro Higashinaka is a scholar working on Artificial Intelligence, Social Psychology and Experimental and Cognitive Psychology. According to data from OpenAlex, Ryuichiro Higashinaka has authored 124 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 115 papers in Artificial Intelligence, 18 papers in Social Psychology and 8 papers in Experimental and Cognitive Psychology. Recurrent topics in Ryuichiro Higashinaka's work include Speech and dialogue systems (93 papers), Topic Modeling (74 papers) and Natural Language Processing Techniques (52 papers). Ryuichiro Higashinaka is often cited by papers focused on Speech and dialogue systems (93 papers), Topic Modeling (74 papers) and Natural Language Processing Techniques (52 papers). Ryuichiro Higashinaka collaborates with scholars based in Japan, United States and United Kingdom. Ryuichiro Higashinaka's co-authors include Hideki Isozaki, Toyomi Meguro, Kohji Dohsaka, Yoshihiro Matsuo, Mikio Nakano, Yasuhiro Minami, Kiyoaki Aikawa, Hiroaki Sugiyama, Yuka Kobayashi and Tôru Hirano and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Access.

In The Last Decade

Ryuichiro Higashinaka

104 papers receiving 919 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ryuichiro Higashinaka Japan 18 905 164 86 76 68 124 1.0k
Lucian Galescu United States 14 729 0.8× 80 0.5× 76 0.9× 62 0.8× 64 0.9× 43 939
Kallirroi Georgila United States 18 933 1.0× 149 0.9× 34 0.4× 104 1.4× 78 1.1× 60 1.1k
Simon Keizer United Kingdom 18 978 1.1× 133 0.8× 40 0.5× 102 1.3× 49 0.7× 58 1.1k
Amy Isard United Kingdom 14 679 0.8× 176 1.1× 35 0.4× 83 1.1× 115 1.7× 48 864
Pierre Lison Norway 12 648 0.7× 68 0.4× 47 0.5× 115 1.5× 22 0.3× 35 760
Antoine Raux United States 18 1.2k 1.3× 155 0.9× 41 0.5× 137 1.8× 101 1.5× 46 1.3k
Paul Piwek United Kingdom 15 523 0.6× 51 0.3× 100 1.2× 80 1.1× 103 1.5× 82 730
Joseph Mariani France 9 479 0.5× 51 0.3× 44 0.5× 50 0.7× 72 1.1× 52 622
Gina‐Anne Levow United States 14 975 1.1× 91 0.6× 56 0.7× 107 1.4× 223 3.3× 78 1.1k
Joseph Polifroni United States 21 1.4k 1.5× 85 0.5× 101 1.2× 76 1.0× 58 0.9× 67 1.5k

Countries citing papers authored by Ryuichiro Higashinaka

Since Specialization
Citations

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

Fields of papers citing papers by Ryuichiro Higashinaka

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ryuichiro Higashinaka

This figure shows the co-authorship network connecting the top 25 collaborators of Ryuichiro Higashinaka. A scholar is included among the top collaborators of Ryuichiro Higashinaka 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 Ryuichiro Higashinaka. Ryuichiro Higashinaka 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.
Higashinaka, Ryuichiro, et al.. (2025). Adapting language generation to dialogue environments and users for task-oriented dialogue systems. SHILAP Revista de lepidopterología. 11. 100153–100153. 2 indexed citations
2.
Higashinaka, Ryuichiro, et al.. (2024). Travel Agency Task Dialogue Corpus: A Multimodal Dataset with Age-Diverse Speakers. ACM Transactions on Asian and Low-Resource Language Information Processing. 23(9). 1–23.
3.
Mochizuki, Shota, et al.. (2024). Clarifying the Dialogue-Level Performance of GPT-3.5 and GPT-4 in Task-Oriented and Non-Task-Oriented Dialogue Systems. Proceedings of the AAAI Symposium Series. 2(1). 182–186. 3 indexed citations
4.
Higashinaka, Ryuichiro, et al.. (2023). Modeling Collaborative Dialogue in Minecraft with Action-Utterance Model. 75–81.
5.
Higashinaka, Ryuichiro, et al.. (2022). Combining Argumentation Structure and Language Model for Generating Natural Argumentative Dialogue. 65–71. 2 indexed citations
6.
Kodama, Takashi, et al.. (2020). Generating Responses that Reflect Meta Information in User-Generated Question Answer Pairs. Language Resources and Evaluation. 5433–5441.
7.
Ishii, Ryo, Ryuichiro Higashinaka, & Junji Tomita. (2018). Predicting Nods by using Dialogue Acts in Dialogue. Language Resources and Evaluation.
8.
Higashinaka, Ryuichiro, et al.. (2018). Refinement of Utterance Database and Concatenation of Utterances for Enhancing System Utterances in Chat-oriented Dialogue System.. International Joint Conference on Artificial Intelligence. 44–51. 1 indexed citations
9.
Masumura, Ryo, Tomohiro Tanaka, Ryuichiro Higashinaka, Hirokazu Masataki, & Yushi Aono. (2018). Multi-task and Multi-lingual Joint Learning of Neural Lexical Utterance Classification based on Partially-shared Modeling.. International Conference on Computational Linguistics. 3586–3596. 5 indexed citations
10.
Higashinaka, Ryuichiro, et al.. (2018). Creating Large-Scale Argumentation Structures for Dialogue Systems. Language Resources and Evaluation. 5 indexed citations
11.
Shang, Lifeng, Tetsuya Sakai, Zhengdong Lu, et al.. (2016). Overview of the NTCIR-12 Short Text Conversation Task.. NTCIR. 15 indexed citations
12.
Matsuo, Yoshihiro, et al.. (2016). Natural Language Processing Supporting Artificial Intelligence. NTT technical review. 14(5). 9–14. 2 indexed citations
13.
Irie, Go, et al.. (2015). Media Processing Technology for Achieving Hospitality in Information Search. NTT technical review. 13(4). 35–44. 2 indexed citations
14.
Imamura, Kenji, Ryuichiro Higashinaka, & Tomoko Izumi. (2014). Predicate-Argument Structure Analysis with Zero-Anaphora Resolution for Dialogue Systems. International Conference on Computational Linguistics. 806–815. 6 indexed citations
15.
Higashinaka, Ryuichiro, Kenji Imamura, Toyomi Meguro, et al.. (2014). Towards an open-domain conversational system fully based on natural language processing. International Conference on Computational Linguistics. 928–939. 103 indexed citations
16.
Meguro, Toyomi, Ryuichiro Higashinaka, Hiroaki Sugiyama, & Yasuhiro Minami. (2013). Dialogue act tagging for microblog utterances using semantic category patterns. 2013.
17.
Sugiyama, Hiroaki, Toyomi Meguro, Ryuichiro Higashinaka, & Yasuhiro Minami. (2013). Open-domain Utterance Generation for Conversational Dialogue Systems using Web-scale Dependency Structures. Annual Meeting of the Special Interest Group on Discourse and Dialogue. 334–338. 20 indexed citations
18.
Higashinaka, Ryuichiro, et al.. (2012). Creating an Extended Named Entity Dictionary from Wikipedia. International Conference on Computational Linguistics. 1163–1178. 11 indexed citations
19.
Higashinaka, Ryuichiro, et al.. (2012). Automatic Detection of Metonymies using Associative Relations between Words. Cognitive Science. 34(34). 1 indexed citations
20.
Higashinaka, Ryuichiro & Hideki Isozaki. (2007). NTT's Question Answering System for NTCIR-6 QAC-4. NTCIR. 4 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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