Layla El Asri
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition
- Social Psychology
- Molecular Biology
- Signal Processing
- Co-authors
- Hannes SchulzShikhar SharmaKaheer SulemanJérémie ZumerJustin HarrisJackie Chi Kit CheungXiujun LiJianfeng Gao
- Topics
- Speech and dialogue systems (4 papers)Topic Modeling (4 papers)Multimodal Machine Learning Applications (3 papers)
- Journals
- arXiv (Cornell University)National Conference on Artificial IntelligenceFindings of the Association for Computational Linguistics: ACL 2022
- Partner nations
- CanadaUnited StatesNetherlands
In The Last Decade
Layla El Asri
5 papers receiving 139 citations
Peers
Comparison fields: 5 of 22
- Artificial Intelligence 144
- Computer Vision and Pattern Recognition 27
- Social Psychology 5
- Molecular Biology 3
- Signal Processing 3
Countries citing papers authored by Layla El Asri
This map shows the geographic impact of Layla El Asri'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 Layla El Asri with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Layla El Asri more than expected).
Fields of papers citing papers by Layla El Asri
This network shows the impact of papers produced by Layla El Asri. 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 Layla El Asri. The network helps show where Layla El Asri may publish in the future.
Co-authorship network of co-authors of Layla El Asri
This figure shows the co-authorship network connecting the top 25 collaborators of Layla El Asri. A scholar is included among the top collaborators of Layla El Asri 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 Layla El Asri. Layla El Asri is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 15 | |
| 2 | From FiLM to Video: Multi-turn Question Answering with Multi-modal Context | 5 |
| 3 | Multi-Domain Task-Completion Dialog Challenge | 17 |
| 4 | Keep Drawing It: Iterative language-based image generation and editing. | 4 |
| 5 | 113 | |
| 6 | Safe Evaluation of Dialogue Management | 0 |
About Layla El Asri
Layla El Asri is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Infectious Diseases, having authored 6 papers that have together received 154 indexed citations. Recurring topics across this work include Speech and dialogue systems (4 papers), Topic Modeling (4 papers) and Multimodal Machine Learning Applications (3 papers). The work is most often cited by research in Artificial Intelligence (144 citations), Computer Vision and Pattern Recognition (27 citations) and Applied Psychology (3 citations). Layla El Asri has collaborated with scholars based in Canada, United States and Netherlands. Frequent co-authors include Hannes Schulz, Shikhar Sharma, Kaheer Suleman, Jérémie Zumer, Justin Harris, Jackie Chi Kit Cheung, Xiujun Li, Jianfeng Gao, Sung‐Jin Lee and Samira Ebrahimi Kahou. Their work appears in journals such as arXiv (Cornell University), National Conference on Artificial Intelligence and Findings of the Association for Computational Linguistics: ACL 2022.
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.