Xinxi Lyu
Impact in
- Health Informatics top 5%
- Artificial Intelligence top 5%
- Topic Modeling
- Natural Language Processing Techniques
- Domain Adaptation and Few-Shot Learning
- Speech and dialogue systems
- Advanced Text Analysis Techniques
- Explainable Artificial Intelligence (XAI)
Papers in
-
- Natural Language Processing Techniques 3
- Topic Modeling 2
- Domain Adaptation and Few-Shot Learning 1
- Machine Learning and Algorithms 1
- Speech Recognition and Synthesis 1
-
- Multimodal Machine Learning Applications 1
- Co-authors
- Hannaneh Hajishirzi (4 shared papers)Sewon Min (4 shared papers)Luke Zettlemoyer (3 shared papers)Mikel Artetxe (1 shared paper)Ari Holtzman (1 shared paper)Kalpesh Krishna (1 shared paper)Mike Lewis (1 shared paper)Wen-tau Yih (1 shared paper)
- Journals
- Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (1 paper)
- Partner nations
- United States
In The Last Decade
Xinxi Lyu
4 papers receiving 507 citations
Xinxi Lyu's Hit Papers
Peers
Comparison fields: 5 of 74
- Health Informatics 21
- Artificial Intelligence 377
- Computer Vision and Pattern Recognition 110
- Information Systems 61
- Software 8
Countries citing papers authored by Xinxi Lyu
This map shows the geographic impact of Xinxi Lyu'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 Xinxi Lyu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xinxi Lyu more than expected).
Fields of papers citing papers by Xinxi Lyu
This network shows the impact of papers produced by Xinxi Lyu. 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 Xinxi Lyu. The network helps show where Xinxi Lyu may publish in the future.
Co-authors
The 19 scholars most cited alongside Xinxi Lyu, 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 | Rethinking the Role of Demonstrations: What Makes In-Context Learning Work? Hit paper breakdown → | 2022 | 403 |
| 2 | 2023 | 95 | |
| 3 | 2022 | 22 | |
| 4 | 2023 | 5 |
About Xinxi Lyu
Xinxi Lyu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Materials Chemistry, Infectious Diseases and Organic Chemistry, having authored 4 papers that have together received 525 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (3 papers), Topic Modeling (2 papers), Machine Learning in Materials Science (1 paper), Domain Adaptation and Few-Shot Learning (1 paper), Machine Learning and Algorithms (1 paper), Multimodal Machine Learning Applications (1 paper) and Speech Recognition and Synthesis (1 paper). The work is most often cited by research in Health Informatics (21 citations), Artificial Intelligence (377 citations), Computer Vision and Pattern Recognition (110 citations), Information Systems (61 citations) and Software (8 citations). Xinxi Lyu has collaborated with scholars based in United States. Frequent co-authors include Hannaneh Hajishirzi, Sewon Min, Luke Zettlemoyer, Mikel Artetxe, Ari Holtzman, Kalpesh Krishna, Mike Lewis, Wen-tau Yih, Mohit Iyyer and Pang Wei Koh. Their work appears in journals such as Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies.
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.