Dani Yogatama
- Artificial Intelligence top 0.5%
- Topic Modeling 25
- Natural Language Processing Techniques 19
- Text and Document Classification Technologies 6
- Sentiment Analysis and Opinion Mining 4
- Speech and dialogue systems 3
- Machine Learning and Algorithms 2
- General Social Sciences top 1%
- Computational and Text Analysis Methods 2
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- Multimodal Machine Learning Applications 5
- Information Systems top 5%
- Co-authors
- Noah A. SmithMichael HeilmanBrendan O’ConnorJacob EisensteinKevin GimpelDipanjan DasNathan SchneiderChris Dyer
- Journals
- Transactions of the Association for Computational Linguistics (4 papers)Natural Language Engineering (1 paper)Empirical Methods in Natural Language Processing (1 paper)
- Partner nations
- United StatesUnited KingdomCanada
In The Last Decade
Dani Yogatama
28 papers receiving 1.7k citations
Hit Papers
Peers
Comparison fields: 5 of 114
- Artificial Intelligence 1.5k
- General Social Sciences 37
- Computer Vision and Pattern Recognition 205
- Information Systems 211
- Health Informatics 9
Countries citing papers authored by Dani Yogatama
This map shows the geographic impact of Dani Yogatama'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 Dani Yogatama with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dani Yogatama more than expected).
Fields of papers citing papers by Dani Yogatama
This network shows the impact of papers produced by Dani Yogatama. 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 Dani Yogatama. The network helps show where Dani Yogatama may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Dani Yogatama, 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 | 2023 | 18 | |
| 2 | 2023 | 1 | |
| 3 | 2023 | 14 | |
| 4 | 2022 | 10 | |
| 5 | End-to-End Training of Multi-Document Reader and Retriever for Open-Domain Question Answering | 2021 | 10 |
| 6 | LiRo: Benchmark and leaderboard for Romanian language tasks | 2021 | 10 |
| 7 | A Mutual Information Maximization Perspective of Language Representation Learning | 2020 | 18 |
| 8 | 2020 | 74 | |
| 9 | 2019 | 64 | |
| 10 | 2018 | 10 | |
| 11 | Memory Architectures in Recurrent Neural Network Language Models | 2018 | 21 |
| 12 | 2018 | 157 | |
| 13 | 2018 | 1 | |
| 14 | 2017 | 155 | |
| 15 | 2015 | 76 | |
| 16 | 2015 | 73 | |
| 17 | Efficient Transfer Learning Method for Automatic Hyperparameter Tuning | 2014 | 82 |
| 18 | 2014 | 13 | |
| 19 | Proceedings of the 49th Annual Meeting of the Association for Computational Linguisticsbreakdown → | 2011 | 743 |
| 20 | Predicting a Scientific Community’s Response to an Article | 2011 | 29 |
About Dani Yogatama
Dani Yogatama is a scholar working on Artificial Intelligence, General Social Sciences and Computer Vision and Pattern Recognition, having authored 30 papers that have together received 1.8k indexed citations. Recurring topics across this work include Topic Modeling (25 papers), Natural Language Processing Techniques (19 papers), Text and Document Classification Technologies (6 papers), Multimodal Machine Learning Applications (5 papers), Sentiment Analysis and Opinion Mining (4 papers), Speech and dialogue systems (3 papers), Computational and Text Analysis Methods (2 papers) and Machine Learning and Algorithms (2 papers). The work is most often cited by research in Artificial Intelligence (1.5k citations), General Social Sciences (37 citations) and Computer Vision and Pattern Recognition (205 citations). Dani Yogatama has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Noah A. Smith, Michael Heilman, Brendan O’Connor, Jacob Eisenstein, Kevin Gimpel, Dipanjan Das, Nathan Schneider, Chris Dyer, D. Quinn Mills and Phil Blunsom. Their work appears in journals such as Transactions of the Association for Computational Linguistics, Natural Language Engineering, Empirical Methods in Natural Language Processing, Proceedings of the International AAAI Conference on Web and Social Media and International Conference on Artificial Intelligence and Statistics.
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.