Telmo Pires
Impact in
- Artificial Intelligence top 2%
- Topic Modeling
- Natural Language Processing Techniques
- Sentiment Analysis and Opinion Mining
- Hate Speech and Cyberbullying Detection
- Speech Recognition and Synthesis
- Text Readability and Simplification
- Advanced Text Analysis Techniques
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- Multimodal Machine Learning Applications
Papers in
-
- Topic Modeling 4
- Natural Language Processing Techniques 3
- Adversarial Robustness in Machine Learning 1
- Speech Recognition and Synthesis 1
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- Data Visualization and Analytics 1
- Advanced Neural Network Applications 1
- Co-authors
- Dan Garrette (1 shared paper)Eva Schlinger (1 shared paper)Hendra Setiawan (2 shared papers)Christian Gollan (1 shared paper)Dominic Telaar (1 shared paper)Orion Weller (1 shared paper)Matthias Sperber (1 shared paper)Matthias Paulik (1 shared paper)
- Journals
- Findings of the Association for Computational Linguistics: ACL 2022 (1 paper)
- Partner nations
- United KingdomUnited StatesPortugal
In The Last Decade
Telmo Pires
7 papers receiving 801 citations
Telmo Pires's Hit Papers
Peers
Comparison fields: 5 of 59
- Artificial Intelligence 767
- Computer Vision and Pattern Recognition 164
- General Social Sciences 11
- Information Systems 69
- Health Informatics 4
Countries citing papers authored by Telmo Pires
This map shows the geographic impact of Telmo Pires'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 Telmo Pires with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Telmo Pires more than expected).
Fields of papers citing papers by Telmo Pires
This network shows the impact of papers produced by Telmo Pires. 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 Telmo Pires. The network helps show where Telmo Pires may publish in the future.
Co-authors
The 9 scholars most cited alongside Telmo Pires, 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 | How Multilingual is Multilingual BERT? Hit paper breakdown → | 2019 | 811 |
| 2 | 2022 | 18 | |
| 3 | 2023 | 7 | |
| 4 | 2022 | 6 | |
| 5 | 2023 | 3 | |
| 6 | 2017 | 2 | |
| 7 | 2024 | 1 |
About Telmo Pires
Telmo Pires is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Insect Science and Renewable Energy, Sustainability and the Environment, having authored 7 papers that have together received 848 indexed citations. Recurring topics across this work include Topic Modeling (4 papers), Natural Language Processing Techniques (3 papers), Adversarial Robustness in Machine Learning (1 paper), Data Visualization and Analytics (1 paper), Time Series Analysis and Forecasting (1 paper), Data Management and Algorithms (1 paper), Speech Recognition and Synthesis (1 paper) and Advanced Neural Network Applications (1 paper). The work is most often cited by research in Artificial Intelligence (767 citations), Computer Vision and Pattern Recognition (164 citations), General Social Sciences (11 citations), Information Systems (69 citations) and Health Informatics (4 citations). Telmo Pires has collaborated with scholars based in United Kingdom, United States and Portugal. Frequent co-authors include Dan Garrette, Eva Schlinger, Hendra Setiawan, Christian Gollan, Dominic Telaar, Orion Weller, Matthias Sperber, Matthias Paulik and Mário A. T. Figueiredo. Their work appears in journals such as 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.