Chris Alberti
- Artificial Intelligence top 1%
- Natural Language Processing Techniques 11
- Topic Modeling 8
- Speech Recognition and Synthesis 3
- Speech and dialogue systems 3
- Text Readability and Simplification 3
- Advanced Text Analysis Techniques 1
- Authorship Attribution and Profiling 1
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- Multimodal Machine Learning Applications 2
- Information Systems top 5%
- Co-authors
- Michael CollinsSlav PetrovJacob DevlinAndrew M. DaiIllia PolosukhinTom KwiatkowskiKristina ToutanovaQuoc V. Le
- Journals
- Transactions of the Association for Computational Linguistics (3 papers)Photogrammetric Engineering & Remote Sensing (1 paper)Computer Speech & Language (1 paper)
- Partner nations
- United StatesUnited KingdomGermany
In The Last Decade
Chris Alberti
12 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 73
- Artificial Intelligence 1.3k
- Computer Vision and Pattern Recognition 492
- Information Systems 187
- Health Informatics 9
- Management Science and Operations Research 48
Countries citing papers authored by Chris Alberti
This map shows the geographic impact of Chris Alberti'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 Chris Alberti with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chris Alberti more than expected).
Fields of papers citing papers by Chris Alberti
This network shows the impact of papers produced by Chris Alberti. 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 Chris Alberti. The network helps show where Chris Alberti may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Chris Alberti, 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 | 2024 | 0 | |
| 2 | 2023 | 12 | |
| 3 | 2023 | 3 | |
| 4 | 2022 | 1 | |
| 5 | 2020 | 148 | |
| 6 | 2019 | 108 | |
| 7 | Natural Questions: A Benchmark for Question Answering Researchbreakdown → | 2019 | 984 |
| 8 | 2015 | 23 | |
| 9 | 2015 | 121 | |
| 10 | 2013 | 1 | |
| 11 | 2011 | 1 | |
| 12 | 2010 | 7 | |
| 13 | 2010 | 5 |
About Chris Alberti
Chris Alberti is a scholar working on Artificial Intelligence, Media Technology, Computer Vision and Pattern Recognition, Signal Processing and Ocean Engineering, having authored 13 papers that have together received 1.4k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (11 papers), Topic Modeling (8 papers), Speech Recognition and Synthesis (3 papers), Speech and dialogue systems (3 papers), Text Readability and Simplification (3 papers), Multimodal Machine Learning Applications (2 papers), Advanced Text Analysis Techniques (1 paper) and Authorship Attribution and Profiling (1 paper). The work is most often cited by research in Artificial Intelligence (1.3k citations), Computer Vision and Pattern Recognition (492 citations), Information Systems (187 citations), Health Informatics (9 citations) and Management Science and Operations Research (48 citations). Chris Alberti has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Michael Collins, Slav Petrov, Jacob Devlin, Andrew M. Dai, Illia Polosukhin, Tom Kwiatkowski, Kristina Toutanova, Quoc V. Le, Ankur P. Parikh and Jennimaria Palomaki. Their work appears in journals such as Transactions of the Association for Computational Linguistics, Photogrammetric Engineering & Remote Sensing and Computer Speech & Language.
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.