Ke Tran

506 total citations
12 papers, 198 citations indexed

About

Ke Tran is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Language and Linguistics. According to data from OpenAlex, Ke Tran has authored 12 papers receiving a total of 198 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 1 paper in Language and Linguistics. Recurrent topics in Ke Tran's work include Natural Language Processing Techniques (12 papers), Topic Modeling (11 papers) and Multimodal Machine Learning Applications (4 papers). Ke Tran is often cited by papers focused on Natural Language Processing Techniques (12 papers), Topic Modeling (11 papers) and Multimodal Machine Learning Applications (4 papers). Ke Tran collaborates with scholars based in Netherlands, United States and Germany. Ke Tran's co-authors include Arianna Bisazza, Christof Monz, Yonatan Bisk, Kristina Toutanova, Saleema Amershi, Chris Brockett, Daniel Marcu, Kevin Knight, Ashish Vaswani and Ming Tan and has published in prestigious journals such as University of Groningen research database (University of Groningen / Centre for Information Technology), UvA-DARE (University of Amsterdam) and Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing.

In The Last Decade

Ke Tran

12 papers receiving 176 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ke Tran Netherlands	7	180	61	14	8	7	12	198
Gustavo Aguilar United States	4	190 1.1×	50 0.8×	12 0.9×	4 0.5×	8 1.1×	9	218
Jasmijn Bastings United States	5	164 0.9×	37 0.6×	15 1.1×	8 1.0×	2 0.3×	8	195
Chulun Zhou China	9	163 0.9×	61 1.0×	22 1.6×	4 0.5×	7 1.0×	17	185
J. Edward Hu United States	5	162 0.9×	50 0.8×	11 0.8×	6 0.8×	5 0.7×	8	170
Yixuan Su United Kingdom	8	184 1.0×	56 0.9×	19 1.4×	12 1.5×	3 0.4×	18	208
Richard Yuanzhe Pang United States	8	190 1.1×	52 0.9×	18 1.3×	7 0.9×	4 0.6×	14	208
Thomas Scialom France	6	158 0.9×	46 0.8×	18 1.3×	5 0.6×	5 0.7×	12	178
Ákos Kádár Netherlands	7	152 0.8×	93 1.5×	5 0.4×	5 0.6×	10 1.4×	17	173
Max Glockner Germany	3	168 0.9×	47 0.8×	15 1.1×	4 0.5×	7 1.0×	4	174
Stephen Merity Australia	2	125 0.7×	91 1.5×	9 0.6×	11 1.4×	4 0.6×	3	152

Countries citing papers authored by Ke Tran

Since Specialization

Citations

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

Fields of papers citing papers by Ke Tran

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ke Tran

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

All Works

Sort: Min cites: Since: Top N: Style:

12 of 12 papers shown

Hasler, Eva, et al.. (2024). The Fine-Tuning Paradox: Boosting Translation Quality Without Sacrificing LLM Abilities. UvA-DARE (University of Amsterdam). 6189–6206. 1 indexed citations

Soltan, Saleh, Víctor Soto, Ke Tran, & Wael Hamza. (2022). A Hybrid Approach to Cross-lingual Product Review Summarization. 18–28. 1 indexed citations

Hasler, Eva, et al.. (2021). Improving the Quality Trade-Off for Neural Machine Translation Multi-Domain Adaptation. Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. 8470–8477. 3 indexed citations

Tran, Ke & Ming Tan. (2020). Generating Synthetic Data for Task-Oriented Semantic Parsing with Hierarchical Representations. 17–21. 3 indexed citations

Tran, Ke & Arianna Bisazza. (2019). Zero-shot Dependency Parsing with Pre-trained Multilingual Sentence Representations. University of Groningen research database (University of Groningen / Centre for Information Technology). 281–288. 14 indexed citations

Tran, Ke, Arianna Bisazza, & Christof Monz. (2018). The Importance of Being Recurrent for Modeling Hierarchical Structure. UvA-DARE (University of Amsterdam). 4731–4736. 64 indexed citations

Bisk, Yonatan & Ke Tran. (2018). Inducing Grammars with and for Neural Machine Translation. 25–35. 8 indexed citations

Tran, Ke, Yonatan Bisk, Ashish Vaswani, Daniel Marcu, & Kevin Knight. (2016). Unsupervised Neural Hidden Markov Models. UvA-DARE (University of Amsterdam). 63–71. 25 indexed citations

Tran, Ke, Arianna Bisazza, & Christof Monz. (2016). Recurrent Memory Networks for Language Modeling. UvA-DARE (University of Amsterdam). 321–331. 40 indexed citations

10.

Toutanova, Kristina, Chris Brockett, Ke Tran, & Saleema Amershi. (2016). A Dataset and Evaluation Metrics for Abstractive Compression of Sentences and Short Paragraphs. UvA-DARE (University of Amsterdam). 340–350. 28 indexed citations

11.

Tran, Ke, Arianna Bisazza, & Christof Monz. (2015). A distributed inflection model for translating into morphologically rich languages. UvA-DARE (University of Amsterdam). 1. 145–159. 2 indexed citations

12.

Tran, Ke, Arianna Bisazza, & Christof Monz. (2014). Word Translation Prediction for Morphologically Rich Languages with Bilingual Neural Networks. UvA-DARE (University of Amsterdam). 1676–1688. 9 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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