Wade Shen

47 papers receiving 4.3k citations

Hit Papers

Moses20072026201320192007200710002.0k3.0k

Peers

Wade Shen
Comparison fields: 5 of 80
  • Artificial Intelligence 4.9k
  • Computer Vision and Pattern Recognition 803
  • Signal Processing 524
  • Molecular Biology 335
  • Information Systems 230
Replace Marcello Federico with:
Marcello Federico Italy
Hitoshi Isahara Japan
Eiichiro Sumita Japan
Lucia Specia United Kingdom
Thorsten Brants Germany
Nicola Bertoldi Italy
Christof Monz Netherlands
Kemal Oflazer Türkiye
Grzegorz Kondrak Canada
Alexei Baevski Israel
Wade Shen relative to Marcello Federico Italy Marcello Federico's profile →
Citations per field
00.5×1.5×2.0×
Marcello Federico · 1×
Citations per year

Countries citing papers authored by Wade Shen

Since Specialization
Citations

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

Fields of papers citing papers by Wade Shen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wade Shen

This figure shows the co-authorship network connecting the top 25 collaborators of Wade Shen. A scholar is included among the top collaborators of Wade Shen 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 Wade Shen. Wade Shen 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
#WorkIndexed citations
1 3
2
End-to-end Training of Differentiable Pipelines Across Machine Learning Frameworks
5
3 3
4 7
5 1
6 29
7 7
8
Bridging the Gap between Linguists and Technology Developers: Large-Scale, Sociolinguistic Annotation for Dialect and Speaker Recognition.
3
9 15
10 17
11 8
12
Moses: Open Source Toolkit for Statistical Machine Translationbreakdown →
1105
13 17
14 3165
15
The JHU Workshop 2006 IWSLT System
11
16
An efficient graph search decoder for phrase-based statistical machine translation.
2
17 30
18
Open Source Toolkit for Statistical Machine Translation: Factored Translation Models and Lattice Decoding
6
19
The MITLL/AFRL MT System
3
20
The Effect of Text Difficulty on Machine Translation Performance -- A Pilot Study with ILR-Rated Texts in Spanish, Farsi, Arabic, Russian and Korean
6

About Wade Shen

Wade Shen is a scholar working on Signal Processing, Artificial Intelligence and Linguistics and Language, having authored 49 papers that have together received 5.0k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (31 papers), Speech Recognition and Synthesis (30 papers) and Music and Audio Processing (15 papers). The work is most often cited by research in Artificial Intelligence (4.9k citations), Signal Processing (524 citations) and Computer Vision and Pattern Recognition (803 citations). Wade Shen has collaborated with scholars based in United States, Germany and Czechia. Frequent co-authors include Marcello Federico, Richard Zens, Nicola Bertoldi, Hieu Hoang, Ondřej Bojar, Philipp Koehn, Chris Dyer, Evan Herbst, Brooke Cowan and Alexandra Constantin. Their work appears in journals such as The Journal of the Acoustical Society of America, IEEE Signal Processing Magazine and IEEE Transactions on Audio Speech and 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.

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