Anton Bakhtin
Impact in
- Artificial Intelligence top 1%
- Topic Modeling
- Natural Language Processing Techniques
- Advanced Graph Neural Networks
- Domain Adaptation and Few-Shot Learning
- Speech Recognition and Synthesis
- Advanced Text Analysis Techniques
- Text Readability and Simplification
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- Multimodal Machine Learning Applications
Papers in
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- Speech Recognition and Synthesis 4
- Natural Language Processing Techniques 4
- Topic Modeling 4
- Artificial Intelligence in Games 1
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- Music and Audio Processing 3
- Co-authors
- Tim Rocktäschel (1 shared paper)Sebastian Riedel (1 shared paper)Yuxiang Wu (1 shared paper)Alexander Miller (1 shared paper)Fabio Petroni (1 shared paper)Patrick Lewis (1 shared paper)Rohit Prabhavalkar (2 shared papers)Kanishka Rao (1 shared paper)
- Journals
- DOAJ (DOAJ: Directory of Open Access Journals) (1 paper)Neural Information Processing Systems (1 paper)arXiv (Cornell University) (2 papers)
- Partner nations
- IsraelUnited StatesRussia
In The Last Decade
Anton Bakhtin
8 papers receiving 1.1k citations
Anton Bakhtin's Hit Papers
Peers
Comparison fields: 5 of 73
- Artificial Intelligence 1.0k
- Computer Vision and Pattern Recognition 308
- Health Informatics 15
- General Social Sciences 19
- Signal Processing 61
Countries citing papers authored by Anton Bakhtin
This map shows the geographic impact of Anton Bakhtin'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 Anton Bakhtin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anton Bakhtin more than expected).
Fields of papers citing papers by Anton Bakhtin
This network shows the impact of papers produced by Anton Bakhtin. 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 Anton Bakhtin. The network helps show where Anton Bakhtin may publish in the future.
Co-authors
The 20 scholars most cited alongside Anton Bakhtin, 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 | Language Models as Knowledge Bases? Hit paper breakdown → | 2019 | 1065 |
| 2 | 2017 | 54 | |
| 3 | 2016 | 27 | |
| 4 | 2020 | 3 | |
| 5 | 2018 | 3 | |
| 6 | Energy-Based Models for Text | 2020 | 2 |
| 7 | Mass spectrometry of metalloporphyrins. 2. Vapor pressure of cobalt, nickel, and copper octaethylporphyrinates | 2010 | 1 |
| 8 | Combining Deep Reinforcement Learning and Search for Imperfect-Information Games | 2020 | 1 |
About Anton Bakhtin
Anton Bakhtin is a scholar working on Artificial Intelligence, Signal Processing, Sociology and Political Science, Management Science and Operations Research and Spectroscopy, having authored 8 papers that have together received 1.2k indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (4 papers), Natural Language Processing Techniques (4 papers), Topic Modeling (4 papers), Music and Audio Processing (3 papers), Artificial Intelligence in Games (1 paper), Computational and Text Analysis Methods (1 paper), Porphyrin and Phthalocyanine Chemistry (1 paper) and Molecular Sensors and Ion Detection (1 paper). The work is most often cited by research in Artificial Intelligence (1.0k citations), Computer Vision and Pattern Recognition (308 citations), Health Informatics (15 citations), General Social Sciences (19 citations) and Signal Processing (61 citations). Anton Bakhtin has collaborated with scholars based in Israel, United States and Russia. Frequent co-authors include Tim Rocktäschel, Sebastian Riedel, Yuxiang Wu, Alexander Miller, Fabio Petroni, Patrick Lewis, Rohit Prabhavalkar, Kanishka Rao, Yanzhang He and Raziel Álvarez. Their work appears in journals such as DOAJ (DOAJ: Directory of Open Access Journals), Neural Information Processing Systems and arXiv (Cornell University).
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.