Laura Rimell
- Artificial Intelligence top 5%
- Molecular Biology
- Computer Vision and Pattern Recognition
- Language and Linguistics top 10%
- Experimental and Cognitive Psychology
- Co-authors
- Stephen ClarkMark SteedmanCarlos Gómez‐RodríguezDouwe KielaJoakim NivreRyan McDonaldIvan VulićJean Maillard
- Topics
- Topic Modeling (22 papers)Natural Language Processing Techniques (22 papers)Text Readability and Simplification (6 papers)
- Journals
- Journal of Biomedical InformaticsComputational LinguisticsLanguage Resources and Evaluation
- Partner nations
- United KingdomUnited StatesAustralia
In The Last Decade
Laura Rimell
27 papers receiving 340 citations
Peers
Comparison fields: 5 of 30
- Artificial Intelligence 363
- Molecular Biology 59
- Computer Vision and Pattern Recognition 43
- Language and Linguistics 29
- Experimental and Cognitive Psychology 16
Countries citing papers authored by Laura Rimell
This map shows the geographic impact of Laura Rimell'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 Laura Rimell with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Laura Rimell more than expected).
Fields of papers citing papers by Laura Rimell
This network shows the impact of papers produced by Laura Rimell. 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 Laura Rimell. The network helps show where Laura Rimell may publish in the future.
Co-authorship network of co-authors of Laura Rimell
This figure shows the co-authorship network connecting the top 25 collaborators of Laura Rimell. A scholar is included among the top collaborators of Laura Rimell 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 Laura Rimell. Laura Rimell 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 | 10 | |
| 3 | 13 | |
| 4 | 3 | |
| 5 | 32 | |
| 6 | 14 | |
| 7 | Evaluation of Simple Distributional Compositional Operations on Longer Texts | 2 |
| 8 | UCAM-CORE: Incorporating structured distributional similarity into STS | 2 |
| 9 | 6 | |
| 10 | Nominal Roots as Event Predicates in English Denominal Conversion Verbs | 11 |
| 11 | 7 | |
| 12 | 7 | |
| 13 | Evaluation of Dependency Parsers on Unbounded Dependencies | 38 |
| 14 | Cambridge: Parser Evaluation Using Textual Entailment by Grammatical Relation Comparison | 6 |
| 15 | Chart Pruning for Fast Lexicalised-Grammar Parsing | 12 |
| 16 | Unbounded Dependency Recovery for Parser Evaluation | 52 |
| 17 | 41 | |
| 18 | 22 | |
| 19 | 2 | |
| 20 | VP-preposing and relative scope | 4 |
About Laura Rimell
Laura Rimell is a scholar working on Artificial Intelligence, Language and Linguistics and Linguistics and Language, having authored 27 papers that have together received 394 indexed citations. Recurring topics across this work include Topic Modeling (22 papers), Natural Language Processing Techniques (22 papers) and Text Readability and Simplification (6 papers). The work is most often cited by research in Artificial Intelligence (363 citations), Language and Linguistics (29 citations) and Computer Vision and Pattern Recognition (43 citations). Laura Rimell has collaborated with scholars based in United Kingdom, United States and Australia. Frequent co-authors include Stephen Clark, Mark Steedman, Carlos Gómez‐Rodríguez, Douwe Kiela, Joakim Nivre, Ryan McDonald, Ivan Vulić, Jean Maillard, Phil Blunsom and Qi Liu. Their work appears in journals such as Journal of Biomedical Informatics, Computational Linguistics and Language Resources and Evaluation.
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.