Iz Beltagy

6.8k total citations · 1 hit paper
17 papers, 1.9k citations indexed

About

Iz Beltagy is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, Iz Beltagy has authored 17 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 6 papers in Computer Vision and Pattern Recognition and 5 papers in Molecular Biology. Recurrent topics in Iz Beltagy's work include Topic Modeling (14 papers), Natural Language Processing Techniques (10 papers) and Multimodal Machine Learning Applications (6 papers). Iz Beltagy is often cited by papers focused on Topic Modeling (14 papers), Natural Language Processing Techniques (10 papers) and Multimodal Machine Learning Applications (6 papers). Iz Beltagy collaborates with scholars based in United States, Mexico and South Korea. Iz Beltagy's co-authors include Arman Cohan, Kyle Lo, Giuseppe Carenini, Xiao Wen, Lucy Lu Wang, Matthew E. Peters, Bailey Kuehl, Ana Marasović, Doug Downey and Jay DeYoung and has published in prestigious journals such as Transactions of the Association for Computational Linguistics, arXiv (Cornell University) and Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).

In The Last Decade

Iz Beltagy

15 papers receiving 1.9k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

SciBERT: A Pretrained Language Model for Scientific Text

2019 1.6k citations Iz Beltagy, Kyle Lo et al. profile →

Peers

Countries citing papers authored by Iz Beltagy

Since Specialization

Citations

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

Fields of papers citing papers by Iz Beltagy

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Iz Beltagy

This figure shows the co-authorship network connecting the top 25 collaborators of Iz Beltagy. A scholar is included among the top collaborators of Iz Beltagy 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 Iz Beltagy. Iz Beltagy is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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17 of 17 papers shown

#	Work	Indexed citations
1	TESS: Text-to-Text Self-Conditioned Simplex Diffusion 2024 ·Rabeeh Karimi Mahabadi, (unknown), (unknown), James Henderson, Iz Beltagy, Matthew E. Peters, Arman Cohan	0
2	FiD-ICL: A Fusion-in-Decoder Approach for Efficient In-Context Learning 2023 ·Qinyuan Ye, Iz Beltagy, Matthew E. Peters, Xiang Ren, Hannaneh Hajishirzi	1
3	Z-ICL: Zero-Shot In-Context Learning with Pseudo-Demonstrations 2023 ·Xinxi Lyu, Sewon Min, Iz Beltagy, Luke Zettlemoyer, Hannaneh Hajishirzi	5
4	Transparency Helps Reveal When Language Models Learn Meaning 2023 ·Transactions of the Association for Computational Linguistics ·Zhaofeng Wu, William Merrill, Hao Peng, Iz Beltagy, Noah A. Smith	4
5	What Language Model to Train if You Have One Million GPU Hours? 2022 ·Teven Le Scao, Thomas J. Wang, Daniel Hesslow, Stas Bekman, (unknown), Stella Biderman, Hady Elsahar, Niklas Muennighoff, Jason Phang, Ofir Press, Colin Raffel, Victor Sanh, Sheng Shen, Lintang Sutawika, (unknown), Zheng Yong, Julien Launay, Iz Beltagy	18
6	MultiVerS: Improving scientific claim verification with weak supervision and full-document context 2022 ·David Wadden, Kyle Lo, Lucy Lu Wang, Arman Cohan, Iz Beltagy, Hannaneh Hajishirzi	19
7	Continued Pretraining for Better Zero- and Few-Shot Promptability 2022 ·Zhaofeng Wu, Robert L. Logan, (unknown), (unknown), Dirk Groeneveld, Sameer Singh, Iz Beltagy	4
8	SciFact-Open: Towards open-domain scientific claim verification 2022 ·David Wadden, Kyle Lo, Bailey Kuehl, Arman Cohan, Iz Beltagy, Lucy Lu Wang, Hannaneh Hajishirzi	14
9	PRIMERA: Pyramid-based Masked Sentence Pre-training for Multi-document Summarization 2022 ·Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) ·Xiao Wen, Iz Beltagy, Giuseppe Carenini, Arman Cohan	64
10	Zero- and Few-Shot NLP with Pretrained Language Models 2022 ·Iz Beltagy, Arman Cohan, Robert K. Logan, Sewon Min, Sameer Singh	14
11	Few-Shot Self-Rationalization with Natural Language Prompts 2022 ·Ana Marasović, Iz Beltagy, Doug Downey, Matthew E. Peters	39
12	A Dataset of Information-Seeking Questions and Answers Anchored in Research Papers 2021 ·Pradeep Dasigi, Kyle Lo, Iz Beltagy, Arman Cohan, Noah A. Smith, Matt Gardner	48
13	MSˆ2: Multi-Document Summarization of Medical Studies 2021 ·Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing ·Jay DeYoung, Iz Beltagy, Madeleine van Zuylen, Bailey Kuehl, Lucy Lu Wang	47
14	Beyond Paragraphs: NLP for Long Sequences 2021 ·Iz Beltagy, Arman Cohan, Hannaneh Hajishirzi, Sewon Min, Matthew E. Peters	5
15	SciBERT: A Pretrained Language Model for Scientific Text breakdown → 2019 ·Iz Beltagy, Kyle Lo, Arman Cohan	1577
16	SciBERT: Pretrained Contextualized Embeddings for Scientific Text 2019 ·Iz Beltagy, Arman Cohan, Kyle Lo	88
17	Improving Distant Supervision with Maxpooled Attention and Sentence-Level Supervision. 2018 ·arXiv (Cornell University) ·Iz Beltagy, Kyle Lo, Waleed Ammar	1

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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