Mike Lewis
- Artificial Intelligence top 0.5%
- Computer Vision and Pattern Recognition top 1%
- Information Systems top 5%
- Control and Systems Engineering top 10%
- Computer Networks and Communications top 10%
- Co-authors
- Luke ZettlemoyerAngela FanYann DauphinLuheng HeMark SteedmanMarjan GhazvininejadJiatao GuStefano Carpin
- Topics
- Topic Modeling (32 papers)Natural Language Processing Techniques (29 papers)Multimodal Machine Learning Applications (11 papers)
- Journals
- Journal of American HistoryAI MagazineTransactions of the Association for Computational Linguistics
- Partner nations
- United StatesIsraelUnited Kingdom
In The Last Decade
Mike Lewis
46 papers receiving 2.8k citations
Hit Papers
Peers
Comparison fields: 5 of 117
- Artificial Intelligence 2.4k
- Computer Vision and Pattern Recognition 932
- Information Systems 213
- Control and Systems Engineering 146
- Computer Networks and Communications 125
Countries citing papers authored by Mike Lewis
This map shows the geographic impact of Mike 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 Mike Lewis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mike Lewis more than expected).
Fields of papers citing papers by Mike Lewis
This network shows the impact of papers produced by Mike 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 Mike Lewis. The network helps show where Mike Lewis may publish in the future.
Co-authorship network of co-authors of Mike Lewis
This figure shows the co-authorship network connecting the top 25 collaborators of Mike Lewis. A scholar is included among the top collaborators of Mike 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 Mike Lewis. Mike 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 | 50 | |
| 2 | 80 | |
| 3 | 39 | |
| 4 | 9 | |
| 5 | 75 | |
| 6 | 60 | |
| 7 | Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks | 2 |
| 8 | Pre-training via Paraphrasing | 23 |
| 9 | Hierarchical Decision Making by Generating and Following Natural Language Instructions | 8 |
| 10 | 145 | |
| 11 | Hierarchical Neural Story Generationbreakdown → | 586 |
| 12 | Generative Question Answering: Learning to Answer the Whole Question. | 28 |
| 13 | Hierarchical Text Generation and Planning for Strategic Dialogue | 10 |
| 14 | 98 | |
| 15 | 88 | |
| 16 | 218 | |
| 17 | 113 | |
| 18 | 19 | |
| 19 | USARSim: Providing a Framework for Multi-Robot Performance Evaluation | NIST | 46 |
| 20 | 13 |
About Mike Lewis
Mike Lewis is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Human-Computer Interaction, having authored 47 papers that have together received 3.1k indexed citations. Recurring topics across this work include Topic Modeling (32 papers), Natural Language Processing Techniques (29 papers) and Multimodal Machine Learning Applications (11 papers). The work is most often cited by research in Artificial Intelligence (2.4k citations), Computer Vision and Pattern Recognition (932 citations) and Health Informatics (24 citations). Mike Lewis has collaborated with scholars based in United States, Israel and United Kingdom. Frequent co-authors include Luke Zettlemoyer, Angela Fan, Yann Dauphin, Luheng He, Mark Steedman, Marjan Ghazvininejad, Jiatao Gu, Stefano Carpin, Yinhan Liu and Naman Goyal. Their work appears in journals such as Journal of American History, AI Magazine and Transactions of the Association for Computational Linguistics.
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.