Hiroaki Hayashi
- Artificial Intelligence top 0.5%
- Computer Vision and Pattern Recognition top 2%
- Information Systems top 2%
- Health Informatics top 1%
- Computer Networks and Communications top 10%
- Co-authors
- Graham NeubigZhengbao JiangPengfei LiuWeizhe YuanJinlan FuZi-Yi DouKeiichirō NasuChenyan Xiong
- Topics
- Topic Modeling (8 papers)Natural Language Processing Techniques (8 papers)Advancements in Photolithography Techniques (3 papers)
- Partner nations
- JapanUnited StatesUnited Kingdom
In The Last Decade
Hiroaki Hayashi
18 papers receiving 2.2k citations
Hit Papers
Peers
Comparison fields: 5 of 144
- Artificial Intelligence 1.6k
- Computer Vision and Pattern Recognition 423
- Information Systems 342
- Health Informatics 120
- Computer Networks and Communications 118
Countries citing papers authored by Hiroaki Hayashi
This map shows the geographic impact of Hiroaki Hayashi'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 Hiroaki Hayashi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hiroaki Hayashi more than expected).
Fields of papers citing papers by Hiroaki Hayashi
This network shows the impact of papers produced by Hiroaki Hayashi. 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 Hiroaki Hayashi. The network helps show where Hiroaki Hayashi may publish in the future.
Co-authorship network of co-authors of Hiroaki Hayashi
This figure shows the co-authorship network connecting the top 25 collaborators of Hiroaki Hayashi. A scholar is included among the top collaborators of Hiroaki Hayashi 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 Hiroaki Hayashi. Hiroaki Hayashi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processingbreakdown → | 2003 |
| 2 | 7 | |
| 3 | 122 | |
| 4 | 29 | |
| 5 | 21 | |
| 6 | 3 | |
| 7 | 21 | |
| 8 | 3 | |
| 9 | Improving Stochastic Gradient Descent with Feedback | 7 |
| 10 | 鉄系超伝導体BaFe 1.85 Co 0.15 As 2 のバンドの軌道特性 | 22 |
| 11 | 2 | |
| 12 | 0 | |
| 13 | 8 | |
| 14 | 10 | |
| 15 | 4 | |
| 16 | 2 | |
| 17 | 10 | |
| 18 | 1 | |
| 19 | 28 |
About Hiroaki Hayashi
Hiroaki Hayashi is a scholar working on Artificial Intelligence, Hardware and Architecture and Electrical and Electronic Engineering, having authored 19 papers that have together received 2.3k indexed citations. Recurring topics across this work include Topic Modeling (8 papers), Natural Language Processing Techniques (8 papers) and Advancements in Photolithography Techniques (3 papers). The work is most often cited by research in Health Informatics (120 citations), Artificial Intelligence (1.6k citations) and Computer Vision and Pattern Recognition (423 citations). Hiroaki Hayashi has collaborated with scholars based in Japan, United States and United Kingdom. Frequent co-authors include Graham Neubig, Zhengbao Jiang, Pengfei Liu, Weizhe Yuan, Jinlan Fu, Zi-Yi Dou, Keiichirō Nasu, Chenyan Xiong, Peng Wang and Jayanth Koushik. Their work appears in journals such as Physical review. B, Condensed matter, Physical Review B and ACM Computing Surveys.
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.