Tom Kwiatkowski
- Artificial Intelligence top 0.5%
- Natural Language Processing Techniques 21
- Topic Modeling 19
- Speech and dialogue systems 7
- Explainable Artificial Intelligence (XAI) 2
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- Multimodal Machine Learning Applications 2
- Information Systems top 5%
- General Social Sciences top 5%
- Computational and Text Analysis Methods 1
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- Wikis in Education and Collaboration 2
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- Language Development and Disorders 2
- Co-authors
- Michael CollinsLuke ZettlemoyerJennimaria PalomakiKenton LeeMing‐Wei ChangKristina ToutanovaEunsol ChoiAnkur P. Parikh
- Journals
- Transactions of the Association for Computational Linguistics (4 papers)The Journal of Physiology (1 paper)Cognition (1 paper)
- Partner nations
- United StatesUnited KingdomFrance
In The Last Decade
Tom Kwiatkowski
21 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 80
- Artificial Intelligence 1.8k
- Computer Vision and Pattern Recognition 601
- Information Systems 236
- Health Informatics 10
- General Social Sciences 16
Countries citing papers authored by Tom Kwiatkowski
This map shows the geographic impact of Tom Kwiatkowski'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 Tom Kwiatkowski with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tom Kwiatkowski more than expected).
Fields of papers citing papers by Tom Kwiatkowski
This network shows the impact of papers produced by Tom Kwiatkowski. 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 Tom Kwiatkowski. The network helps show where Tom Kwiatkowski may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Tom Kwiatkowski, 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 | 1 | |
| 3 | 2023 | 1 | |
| 4 | 2022 | 16 | |
| 5 | Empirical Evaluation of Pretraining Strategies for Supervised Entity Linking | 2020 | 6 |
| 6 | Inherent Disagreements in Human Textual Inferences | 2020 | 2 |
| 7 | 2020 | 177 | |
| 8 | Learning Entity Representations for Few-Shot Reconstruction of Wikipedia Categories | 2019 | 2 |
| 9 | 2019 | 112 | |
| 10 | 2019 | 140 | |
| 11 | Natural Questions: A Benchmark for Question Answering Researchbreakdown → | 2019 | 984 |
| 12 | 2018 | 22 | |
| 13 | 2017 | 42 | |
| 14 | 2015 | 17 | |
| 15 | 2014 | 18 | |
| 16 | 2013 | 142 | |
| 17 | Combinatory Categorial Grammars for Robust Natural Language Processing | 2013 | 1 |
| 18 | A Probabilistic Model of Syntactic and Semantic Acquisition from Child-Directed Utterances and their Meanings | 2012 | 47 |
| 19 | 2012 | 12 | |
| 20 | Lexical Generalization in CCG Grammar Induction for Semantic Parsing | 2011 | 101 |
About Tom Kwiatkowski
Tom Kwiatkowski is a scholar working on Artificial Intelligence, General Social Sciences, Communication, Developmental and Educational Psychology and Information Systems, having authored 22 papers that have together received 1.9k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (21 papers), Topic Modeling (19 papers), Speech and dialogue systems (7 papers), Explainable Artificial Intelligence (XAI) (2 papers), Wikis in Education and Collaboration (2 papers), Multimodal Machine Learning Applications (2 papers), Language Development and Disorders (2 papers) and Computational and Text Analysis Methods (1 paper). The work is most often cited by research in Artificial Intelligence (1.8k citations), Computer Vision and Pattern Recognition (601 citations), Information Systems (236 citations), Health Informatics (10 citations) and General Social Sciences (16 citations). Tom Kwiatkowski has collaborated with scholars based in United States, United Kingdom and France. Frequent co-authors include Michael Collins, Luke Zettlemoyer, Jennimaria Palomaki, Kenton Lee, Ming‐Wei Chang, Kristina Toutanova, Eunsol Choi, Ankur P. Parikh, Mark Steedman and Ellie Pavlick. Their work appears in journals such as Transactions of the Association for Computational Linguistics, The Journal of Physiology, Cognition, Edinburgh Research Explorer (University of Edinburgh) and Meeting of the Association for Computational Linguistics.
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.