Steve DeNeefe
Impact in
- Artificial Intelligence top 2%
- Natural Language Processing Techniques
- Topic Modeling
- Speech and dialogue systems
- Text Readability and Simplification
- Algorithms and Data Compression
- Semantic Web and Ontologies
- Speech Recognition and Synthesis
Papers in
-
- Natural Language Processing Techniques 12
- Topic Modeling 11
- Text Readability and Simplification 3
- Algorithms and Data Compression 3
- Semantic Web and Ontologies 2
- Speech and dialogue systems 2
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- Software Engineering Research 2
- Co-authors
- Kevin Knight (7 shared papers)Wei Wang (2 shared papers)Daniel Marcu (2 shared papers)Michel Galley (1 shared paper)Jonathan Graehl (1 shared paper)David Chiang (2 shared papers)Hwee Tou Ng (1 shared paper)Yee Seng Chan (1 shared paper)
- Journals
- University of Southern California Digital Library (1 paper)Columbia Academic Commons (Columbia University) (1 paper)IWSLT (1 paper)Empirical Methods in Natural Language Processing (1 paper)National University of Singapore (1 paper)
- Partner nations
- United StatesGermanySingapore
In The Last Decade
Steve DeNeefe
12 papers receiving 416 citations
Peers
Comparison fields: 5 of 13
- Artificial Intelligence 492
- Computer Vision and Pattern Recognition 48
- Computational Theory and Mathematics 18
- Information Systems 14
- Hardware and Architecture 4
Countries citing papers authored by Steve DeNeefe
This map shows the geographic impact of Steve DeNeefe'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 Steve DeNeefe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Steve DeNeefe more than expected).
Fields of papers citing papers by Steve DeNeefe
This network shows the impact of papers produced by Steve DeNeefe. 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 Steve DeNeefe. The network helps show where Steve DeNeefe may publish in the future.
Co-authors
The 14 scholars most cited alongside Steve DeNeefe, 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 | 2006 | 310 | |
| 2 | What Can Syntax-Based MT Learn from Phrase-Based MT? | 2007 | 62 |
| 3 | 2009 | 38 | |
| 4 | 2008 | 37 | |
| 5 | Two Easy Improvements to Lexical Weighting | 2011 | 20 |
| 6 | 2005 | 9 | |
| 7 | Overcoming Vocabulary Sparsity in MT Using Lattices | 2008 | 7 |
| 8 | 2021 | 7 | |
| 9 | A Decoder for Probabilistic Synchronous Tree Insertion Grammars | 2010 | 2 |
| 10 | 2024 | 1 | |
| 11 | 2023 | 1 | |
| 12 | ISI's 2005 statistical machine translation entries. | 2005 | 1 |
| 13 | 2015 | 0 |
About Steve DeNeefe
Steve DeNeefe is a scholar working on Artificial Intelligence, Information Systems, Molecular Biology, Infectious Diseases and Organic Chemistry, having authored 13 papers that have together received 495 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (12 papers), Topic Modeling (11 papers), Text Readability and Simplification (3 papers), Algorithms and Data Compression (3 papers), Software Engineering Research (2 papers), Semantic Web and Ontologies (2 papers), Speech and dialogue systems (2 papers) and DNA and Biological Computing (1 paper). The work is most often cited by research in Artificial Intelligence (492 citations), Computer Vision and Pattern Recognition (48 citations), Computational Theory and Mathematics (18 citations), Information Systems (14 citations) and Hardware and Architecture (4 citations). Steve DeNeefe has collaborated with scholars based in United States, Germany and Singapore. Frequent co-authors include Kevin Knight, Wei Wang, Daniel Marcu, Michel Galley, Jonathan Graehl, David Chiang, Hwee Tou Ng, Yee Seng Chan, Melissa Roemmele and Ulf Hermjakob. Their work appears in journals such as University of Southern California Digital Library, Columbia Academic Commons (Columbia University), IWSLT, Empirical Methods in Natural Language Processing and National University of Singapore.
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.