Philip Arthur
Impact in
- Artificial Intelligence top 10%
- Natural Language Processing Techniques
- Topic Modeling
- Text Readability and Simplification
- Speech Recognition and Synthesis
- Speech and dialogue systems
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- Multimodal Machine Learning Applications
- Handwritten Text Recognition Techniques
Papers in
-
- Natural Language Processing Techniques 11
- Topic Modeling 10
- Text Readability and Simplification 2
- Semantic Web and Ontologies 2
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- Multimodal Machine Learning Applications 3
- Handwritten Text Recognition Techniques 2
- Co-authors
- Graham Neubig (8 shared papers)Satoshi Nakamura (5 shared papers)Xinyi Wang (2 shared papers)Hieu Pham (1 shared paper)Tomoki Toda (3 shared papers)Sakriani Sakti (3 shared papers)Lucas Ondel (1 shared paper)Qi Ye (1 shared paper)
- Journals
- IEEE/ACM Transactions on Audio Speech and Language Processing (1 paper)Transactions of the Association for Computational Linguistics (1 paper)Monash University Research Portal (Monash University) (3 papers)Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (1 paper)
- Partner nations
- United StatesJapanUnited Kingdom
In The Last Decade
Philip Arthur
13 papers receiving 153 citations
Peers
Comparison fields: 5 of 22
- Artificial Intelligence 161
- Computer Vision and Pattern Recognition 85
- Signal Processing 6
- Language and Linguistics 4
- Radiation 3
Countries citing papers authored by Philip Arthur
This map shows the geographic impact of Philip Arthur'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 Philip Arthur with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Philip Arthur more than expected).
Fields of papers citing papers by Philip Arthur
This network shows the impact of papers produced by Philip Arthur. 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 Philip Arthur. The network helps show where Philip Arthur may publish in the future.
Co-authors
The 25 scholars most cited alongside Philip Arthur, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 101 | |
| 2 | Multilingual neural machine translation with soft decoupled encoding | 2019 | 16 |
| 3 | XNMT: the eXtensible Neural Machine Translation toolkit | 2018 | 13 |
| 4 | 2020 | 11 | |
| 5 | 2017 | 7 | |
| 6 | 2015 | 5 | |
| 7 | 2015 | 4 | |
| 8 | NAIST at the CLEF 2013 QA4MRE pilot task | 2013 | 4 |
| 9 | 2021 | 3 | |
| 10 | 2014 | 3 | |
| 11 | Inter-sentence features and thresholded minimum error rate training: NAIST at CLEF 2013 QA4MRE | 2013 | 2 |
| 12 | 2021 | 2 | |
| 13 | 2012 | 1 |
About Philip Arthur
Philip Arthur is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Radiation, Molecular Biology and Nuclear and High Energy Physics, having authored 13 papers that have together received 172 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (11 papers), Topic Modeling (10 papers), Multimodal Machine Learning Applications (3 papers), Text Readability and Simplification (2 papers), Handwritten Text Recognition Techniques (2 papers), Nuclear Physics and Applications (2 papers), Radiation Detection and Scintillator Technologies (2 papers) and Semantic Web and Ontologies (2 papers). The work is most often cited by research in Artificial Intelligence (161 citations), Computer Vision and Pattern Recognition (85 citations), Signal Processing (6 citations), Language and Linguistics (4 citations) and Radiation (3 citations). Philip Arthur has collaborated with scholars based in United States, Japan and United Kingdom. Frequent co-authors include Graham Neubig, Satoshi Nakamura, Xinyi Wang, Hieu Pham, Tomoki Toda, Sakriani Sakti, Lucas Ondel, Qi Ye, Sarguna Janani Padmanabhan and John Hewitt. Their work appears in journals such as IEEE/ACM Transactions on Audio Speech and Language Processing, Transactions of the Association for Computational Linguistics, Monash University Research Portal (Monash University) and Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing.
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.