Yanai Elazar

1.8k total citations
22 papers, 505 citations indexed

About

Yanai Elazar is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and General Social Sciences. According to data from OpenAlex, Yanai Elazar has authored 22 papers receiving a total of 505 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Artificial Intelligence, 6 papers in Computer Vision and Pattern Recognition and 2 papers in General Social Sciences. Recurrent topics in Yanai Elazar's work include Topic Modeling (17 papers), Natural Language Processing Techniques (12 papers) and Text Readability and Simplification (4 papers). Yanai Elazar is often cited by papers focused on Topic Modeling (17 papers), Natural Language Processing Techniques (12 papers) and Text Readability and Simplification (4 papers). Yanai Elazar collaborates with scholars based in Israel, United States and France. Yanai Elazar's co-authors include Yoav Goldberg, Shauli Ravfogel, Alon Jacovi, Hinrich Schütze, Abhilasha Ravichander, Eduard Hovy, Nora Kassner, Dan Roth, Tiago Pimentel and Xikun Zhang and has published in prestigious journals such as Nature Machine Intelligence, Transactions of the Association for Computational Linguistics and Research at the University of Copenhagen (University of Copenhagen).

In The Last Decade

Yanai Elazar

21 papers receiving 477 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Yanai Elazar Israel 11 433 95 37 27 20 22 505
Anna Rogers United States 11 299 0.7× 67 0.7× 26 0.7× 14 0.5× 25 1.3× 23 370
Faisal Ladhak United States 9 303 0.7× 74 0.8× 23 0.6× 37 1.4× 27 1.4× 14 443
Esin Durmus United States 10 280 0.6× 51 0.5× 32 0.9× 40 1.5× 45 2.3× 18 432
Albert Webson United States 5 342 0.8× 71 0.7× 46 1.2× 9 0.3× 14 0.7× 6 434
Rishi Bommasani United States 7 330 0.8× 36 0.4× 40 1.1× 34 1.3× 19 0.9× 15 435
Daniel Hershcovich Denmark 12 570 1.3× 52 0.5× 103 2.8× 11 0.4× 28 1.4× 54 646
Timo Schick Germany 9 412 1.0× 95 1.0× 50 1.4× 15 0.6× 16 0.8× 13 466
Ilia Shumailov United Kingdom 8 188 0.4× 38 0.4× 68 1.8× 40 1.5× 53 2.6× 19 396
Jonathan Herzig Israel 13 601 1.4× 151 1.6× 67 1.8× 5 0.2× 32 1.6× 25 726
Niklas Muennighoff United States 6 302 0.7× 55 0.6× 37 1.0× 5 0.2× 10 0.5× 8 379

Countries citing papers authored by Yanai Elazar

Since Specialization
Citations

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

Fields of papers citing papers by Yanai Elazar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yanai Elazar

This figure shows the co-authorship network connecting the top 25 collaborators of Yanai Elazar. A scholar is included among the top collaborators of Yanai Elazar based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yanai Elazar. Yanai Elazar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Lyu, Qing, Kumar Shridhar, Chaitanya Malaviya, et al.. (2025). Calibrating Large Language Models with Sample Consistency. Proceedings of the AAAI Conference on Artificial Intelligence. 39(18). 19260–19268. 1 indexed citations
3.
Singh, Sameer, et al.. (2024). The Bias Amplification Paradox in Text-to-Image Generation. 6367–6384. 9 indexed citations
4.
Merrill, William, Noah A. Smith, & Yanai Elazar. (2024). Evaluating n-Gram Novelty of Language Models Using Rusty-DAWG. 14459–14473. 1 indexed citations
5.
Elazar, Yanai, et al.. (2024). Detection and Measurement of Syntactic Templates in Generated Text. 6416–6431. 1 indexed citations
6.
Mosbach, Marius, Tiago Pimentel, Shauli Ravfogel, Dietrich Klakow, & Yanai Elazar. (2023). Few-shot Fine-tuning vs. In-context Learning: A Fair Comparison and Evaluation. 12284–12314. 34 indexed citations
7.
Hupkes, Dieuwke, Mario Giulianelli, Verna Dankers, et al.. (2023). A taxonomy and review of generalization research in NLP. Nature Machine Intelligence. 5(10). 1161–1174. 29 indexed citations
8.
Goldberg, Yoav, et al.. (2022). Lexical Generalization Improves with Larger Models and Longer Training. 4398–4410. 3 indexed citations
9.
Elazar, Yanai, et al.. (2022). Text-based NP Enrichment. Transactions of the Association for Computational Linguistics. 10. 764–784. 4 indexed citations
10.
Elazar, Yanai, Hongming Zhang, Yoav Goldberg, & Dan Roth. (2021). Back to Square One: Artifact Detection, Training and Commonsense Disentanglement in the Winograd Schema. Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. 10486–10500. 17 indexed citations
11.
Elazar, Yanai, Nora Kassner, Shauli Ravfogel, et al.. (2021). Measuring and Improving Consistency in Pretrained Language Models. Transactions of the Association for Computational Linguistics. 9. 1012–1031. 112 indexed citations
12.
Elazar, Yanai, et al.. (2021). Revisiting Few-shot Relation Classification: Evaluation Data and Classification Schemes. Transactions of the Association for Computational Linguistics. 9. 691–706. 20 indexed citations
13.
Elazar, Yanai, Shauli Ravfogel, Alon Jacovi, & Yoav Goldberg. (2021). Amnesic Probing: Behavioral Explanation with Amnesic Counterfactuals. Transactions of the Association for Computational Linguistics. 9. 160–175. 63 indexed citations
14.
Elazar, Yanai, Shauli Ravfogel, Alon Jacovi, & Yoav Goldberg. (2020). When Bert Forgets How To POS: Amnesic Probing of Linguistic Properties and MLM Predictions. arXiv (Cornell University). 10 indexed citations
15.
Zhang, Xikun, Deepak Ramachandran, Ian Tenney, Yanai Elazar, & Dan Roth. (2020). Do Language Embeddings capture Scales?. 292–299. 13 indexed citations
16.
Zhang, Xikun, Deepak Ramachandran, Ian Tenney, Yanai Elazar, & Dan Roth. (2020). Do Language Embeddings capture Scales?. 4889–4896. 26 indexed citations
17.
Elazar, Yanai & Yoav Goldberg. (2019). Where’s My Head? Definition, Data Set, and Models for Numeric Fused-Head Identification and Resolution. Transactions of the Association for Computational Linguistics. 7. 519–535. 9 indexed citations
18.
Barrett, Maria, Yova Kementchedjhieva, Yanai Elazar, Desmond Elliott, & Anders Søgaard. (2019). Adversarial Removal of Demographic Attributes Revisited. Research at the University of Copenhagen (University of Copenhagen). 6329–6334. 19 indexed citations
19.
Resheff, Yehezkel S., Yanai Elazar, Moni Shahar, & Oren Sar Shalom. (2018). Privacy-Adversarial User Representations in Recommender Systems.. arXiv (Cornell University). 1 indexed citations
20.
Elazar, Yanai & Yoav Goldberg. (2018). Adversarial Removal of Demographic Attributes from Text Data. 11–21. 129 indexed citations

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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