William D. Lewis
About
In The Last Decade
William D. Lewis
47 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 84
- Artificial Intelligence 753
- Developmental and Educational Psychology 289
- Cognitive Neuroscience 250
- Experimental and Cognitive Psychology 183
- Social Psychology 109
Countries citing papers authored by William D. Lewis
This map shows the geographic impact of William D. Lewis'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 William D. Lewis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites William D. Lewis more than expected).
Fields of papers citing papers by William D. Lewis
This network shows the impact of papers produced by William D. Lewis. 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 William D. Lewis. The network helps show where William D. Lewis may publish in the future.
Co-authorship network of co-authors of William D. Lewis
This figure shows the co-authorship network connecting the top 25 collaborators of William D. Lewis. A scholar is included among the top collaborators of William D. Lewis 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 William D. Lewis. William D. Lewis is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Applying cross-entropy difference for selecting parallel training data from publicly available sources for conversational machine translation. | 4 |
| 2 | Enriching ODIN | 2 |
| 3 | Dramatically Reducing Training Data Size Through Vocabulary Saturation | 12 |
| 4 | Enhanced and Portable Dependency Projection Algorithms Using Interlinear Glossed Text | 4 |
| 5 | Length of Textual Response as a Construct-Irrelevant Response Strategy: The Case of Shell Language. Research Report. ETS RR-13-07. | 3 |
| 6 | Applications of Data Selection via Cross-Entropy Difference for Real-World Statistical Machine Translation | 4 |
| 7 | Building MT for a Severely Under-Resourced Language: White Hmong | 5 |
| 8 | Improving Dependency Parsing with Interlinear Glossed Text and Syntactic Projection | 5 |
| 9 | Measuring the Divergence of Dependency Structures Cross-Linguistically to Improve Syntactic Projection Algorithms | 6 |
| 10 | Crisis MT: Developing A Cookbook for MT in Crisis Situations | 34 |
| 11 | Comparing Language Similarity across Genetic and Typologically-Based Groupings | 21 |
| 12 | Achieving Domain Specificity in SMT without Overt Siloing | 4 |
| 13 | The Problems of Language Identification within Hugely Multilingual Data Sets. | 5 |
| 14 | Intelligent Selection of Language Model Training Data breakdown → | 324 |
| 15 | Repurposing Theoretical Linguistic Data for Tool Development and Search | 9 |
| 16 | Automatically Identifying Computationally Relevant Typological Features | 25 |
| 17 | Multilingual Structural Projection across Interlinear Text | 31 |
| 18 | The University of Washington's UWCLMAQA System | 2 |
| 19 | Development and Validation of a Comprehensive Real Time AH-64 Apache Simulation Model | 2 |
| 20 | Performance and Handling Qualities Criteria for Low Cost Real Time Rotorcraft Simulators - A Methodology Development | 2 |
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.