Jonathan Berant

8.7k citations
63 papers · 3.0k indexed · 3 hit papers · h-index 22

Impact in

Papers in

Jonathan Berant

59 papers receiving 2.8k citations

Hit Papers

Learning To Retrieve Prompts for In-Context Learning 2022 · 197 citations
1970+4+8Years since publication250500750

Peers

Jonathan Berant
Comparison fields: 5 of 84
  • Artificial Intelligence 2.8k
  • Computer Vision and Pattern Recognition 794
  • Information Systems 397
  • Health Informatics 16
  • Management Science and Operations Research 116
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Citations per field
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Citations per year

Countries citing papers authored by Jonathan Berant

Since Specialization
Citations

This map shows the geographic impact of Jonathan Berant'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 Jonathan Berant with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonathan Berant more than expected).

Fields of papers citing papers by Jonathan Berant

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jonathan Berant. 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 Jonathan Berant. The network helps show where Jonathan Berant may publish in the future.

Co-authors

The 25 scholars most cited alongside Jonathan Berant, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jonathan Berant Line = papers co-authored together Jonathan Berant links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 63 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Semantic Parsing on Freebase from Question-Answer Pairs
Hit paper breakdown →
2013804
2
Semantic Parsing via Paraphrasing
Hit paper breakdown →
2014297
3
2019237
4
Learning To Retrieve Prompts for In-Context Learning
Hit paper breakdown →
2022197
5 2017187
6 2015167
7 2014119
8 202183
9
Global Learning of Typed Entailment Rules
201180
10 201779
11 201961
12 202056
13 202143
14
Global Learning of Focused Entailment Graphs
201040
15 201537
16
Crowdsourcing Inference-Rule Evaluation
201228
17 201128
18 202227
19 201425
20 202324

About Jonathan Berant

Jonathan Berant is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Molecular Biology and Computer Science Applications, having authored 63 papers that have together received 3.0k indexed citations. Recurring topics across this work include Topic Modeling (50 papers), Natural Language Processing Techniques (49 papers), Multimodal Machine Learning Applications (17 papers), Semantic Web and Ontologies (16 papers), Speech and dialogue systems (4 papers), Text Readability and Simplification (3 papers), Software Engineering Research (2 papers) and Mobile Crowdsensing and Crowdsourcing (2 papers). The work is most often cited by research in Artificial Intelligence (2.8k citations), Computer Vision and Pattern Recognition (794 citations), Information Systems (397 citations), Health Informatics (16 citations) and Management Science and Operations Research (116 citations). Jonathan Berant has collaborated with scholars based in Israel, United States and Germany. Frequent co-authors include Percy Liang, Andrew Chou, Roy Frostig, Jonathan Herzig, Ido Dagan, Ohad Rubin, Alon Talmor, Jacob Goldberger, Nicholas Lourie and Yushi Wang. Their work appears in journals such as Transactions of the Association for Computational Linguistics, Theory and applications of categories, Computational Linguistics, Journal of Artificial Intelligence Research and Biomedical Signal Processing and Control.

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.

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