Peyman Passban

435 total citations
14 papers, 183 citations indexed

About

Peyman Passban is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Language and Linguistics. According to data from OpenAlex, Peyman Passban has authored 14 papers receiving a total of 183 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 6 papers in Computer Vision and Pattern Recognition and 1 paper in Language and Linguistics. Recurrent topics in Peyman Passban's work include Natural Language Processing Techniques (13 papers), Topic Modeling (12 papers) and Multimodal Machine Learning Applications (4 papers). Peyman Passban is often cited by papers focused on Natural Language Processing Techniques (13 papers), Topic Modeling (12 papers) and Multimodal Machine Learning Applications (4 papers). Peyman Passban collaborates with scholars based in Ireland, Sweden and Germany. Peyman Passban's co-authors include Qun Liu, Mehdi Rezagholizadeh, Andy Way, Alberto Poncelas, Dimitar Shterionov, Qun Liu, Tanya Roosta, Ashutosh Gupta, Clement Chung and Chris Hokamp and has published in prestigious journals such as SHILAP Revista de lepidopterología, ACM Transactions on Asian and Low-Resource Language Information Processing and Arrow@dit (Dublin Institute of Technology).

In The Last Decade

Peyman Passban

13 papers receiving 166 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Peyman Passban Ireland 7 150 82 9 8 6 14 183
Gustavo Aguilar United States 4 190 1.3× 50 0.6× 4 0.4× 12 1.5× 4 0.7× 9 218
Chenglin Wu China 6 150 1.0× 197 2.4× 4 0.4× 11 1.4× 3 0.5× 7 254
George Kour Israel 4 170 1.1× 51 0.6× 12 1.3× 22 2.8× 5 0.8× 8 213
P J Antony India 11 217 1.4× 86 1.0× 4 0.4× 7 0.9× 13 2.2× 23 259
Philipp Dufter Germany 6 149 1.0× 63 0.8× 9 1.0× 5 0.6× 5 0.8× 17 195
Fabrice Muhlenbach France 6 98 0.7× 38 0.5× 14 1.6× 12 1.5× 3 0.5× 14 141
Jiangtong Li China 10 165 1.1× 160 2.0× 8 0.9× 12 1.5× 8 1.3× 16 266
Yunsu Kim Germany 8 143 1.0× 50 0.6× 13 1.4× 14 1.8× 24 168
Mohamed Farouk Abdel Hady Germany 6 116 0.8× 47 0.6× 6 0.7× 5 0.6× 6 1.0× 12 139

Countries citing papers authored by Peyman Passban

Since Specialization
Citations

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

Fields of papers citing papers by Peyman Passban

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Peyman Passban

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

All Works

14 of 14 papers shown
1.
Passban, Peyman, et al.. (2022). Training Mixed-Domain Translation Models via Federated Learning. Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 2576–2586. 7 indexed citations
2.
Passban, Peyman, et al.. (2022). From Fully Trained to Fully Random Embeddings: Improving Neural Machine Translation with Compact Word Embedding Tables. Proceedings of the AAAI Conference on Artificial Intelligence. 36(10). 10930–10937. 2 indexed citations
3.
Passban, Peyman, et al.. (2021). ALP-KD: Attention-Based Layer Projection for Knowledge Distillation. Proceedings of the AAAI Conference on Artificial Intelligence. 35(15). 13657–13665. 76 indexed citations
4.
Passban, Peyman, et al.. (2020). Why Skip If You Can Combine: A Simple Knowledge Distillation Technique for Intermediate Layers. 1016–1021. 16 indexed citations
5.
Passban, Peyman, Qun Liu, & Andy Way. (2018). Improving character-based decoding using target-side morphological\ninformation for neural machine translation. Arrow@dit (Dublin Institute of Technology). 9 indexed citations
6.
Passban, Peyman, Andy Way, & Qun Liu. (2018). Tailoring Neural Architectures for Translating from Morphologically Rich Languages. International Conference on Computational Linguistics. 3134–3145. 4 indexed citations
7.
Poncelas, Alberto, et al.. (2018). Investigating Backtranslation in Neural Machine Translation. Arrow@dit (Dublin Institute of Technology). 249–258. 31 indexed citations
8.
Passban, Peyman, Qun Liu, & Andy Way. (2017). Translating Low-Resource Languages by Vocabulary Adaptation from Close Counterparts. ACM Transactions on Asian and Low-Resource Language Information Processing. 16(4). 1–14. 16 indexed citations
9.
Passban, Peyman, Qun Liu, & Andy Way. (2017). Providing Morphological Information for SMT Using Neural Networks. SHILAP Revista de lepidopterología. 108(1). 271–282. 5 indexed citations
10.
Passban, Peyman, Qun Liu, & Andy Way. (2016). Enriching Phrase Tables for Statistical Machine Translation Using Mixed Embeddings. International Conference on Computational Linguistics. 2582–2591. 4 indexed citations
11.
Passban, Peyman, Qun Liu, & Andy Way. (2016). Boosting Neural POS Tagger for Farsi Using Morphological Information. ACM Transactions on Asian and Low-Resource Language Information Processing. 16(1). 1–15. 6 indexed citations
12.
Passban, Peyman, Chris Hokamp, Andy Way, & Qun Liu. (2016). Improving Phrase-Based SMT Using Cross-Granularity Embedding Similarity. 129–140. 1 indexed citations
13.
Passban, Peyman, Andy Way, & Qun Liu. (2015). Benchmarking SMT Performance for Farsi Using the TEP++ Corpus. 82–88. 4 indexed citations
14.
Passban, Peyman, et al.. (2012). Developing a shuffle grammar for parsing Arabic verbs. 256–260. 2 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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