Contextual String Embeddings for Sequence Labeling
Impact in
Classified as
- Journal
- International Conference on Computational Linguistics
In The Last Decade
doi.org/w3091852 →Countries where authors are citing Contextual String Embeddings for Sequence Labeling
This map shows the geographic impact of Contextual String Embeddings for Sequence Labeling. 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 Contextual String Embeddings for Sequence Labeling with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Contextual String Embeddings for Sequence Labeling more than expected).
Fields of papers citing Contextual String Embeddings for Sequence Labeling
This network shows the impact of Contextual String Embeddings for Sequence Labeling. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Contextual String Embeddings for Sequence Labeling.
About Contextual String Embeddings for Sequence Labeling
This paper, published in 2018, received 503 indexed citations . Written by Alan Akbik, Duncan A. J. Blythe and Roland Vollgraf covering the research area of Artificial Intelligence. It is primarily cited by scholars working on Artificial Intelligence (462 citations), Molecular Biology (64 citations), Information Systems (58 citations), Management Science and Operations Research (52 citations) and Computer Vision and Pattern Recognition (45 citations). Published in International Conference on 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.
This paper is also available at doi.org/w3091852.