Eran Yahav

6.5k total citations · 1 hit paper
109 papers, 2.9k citations indexed

About

Eran Yahav is a scholar working on Artificial Intelligence, Computer Networks and Communications and Information Systems. According to data from OpenAlex, Eran Yahav has authored 109 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 57 papers in Artificial Intelligence, 43 papers in Computer Networks and Communications and 41 papers in Information Systems. Recurrent topics in Eran Yahav's work include Software Engineering Research (37 papers), Logic, programming, and type systems (36 papers) and Parallel Computing and Optimization Techniques (34 papers). Eran Yahav is often cited by papers focused on Software Engineering Research (37 papers), Logic, programming, and type systems (36 papers) and Parallel Computing and Optimization Techniques (34 papers). Eran Yahav collaborates with scholars based in Israel, United States and Switzerland. Eran Yahav's co-authors include Martin Vechev, Yaniv David, Veselin Raychev, Nimrod Partush, Stephen J. Fink, Sharon Shoham, G. Ramalingam, Greta Yorsh, Marco Pistoia and Nurit Dor and has published in prestigious journals such as IEEE Transactions on Software Engineering, Machine Learning and ACM SIGPLAN Notices.

In The Last Decade

Eran Yahav

105 papers receiving 2.8k 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.

Code completion with statistical language models

2014 336 citations Veselin Raychev, Martin Vechev et al. profile →

Peers

Countries citing papers authored by Eran Yahav

Since Specialization

Citations

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

Fields of papers citing papers by Eran Yahav

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eran Yahav

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

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	On the Expressivity Role of LayerNorm in Transformers’ Attention 2023 ·Shaked Brody, Uri Alon, Eran Yahav	5
2	Towards AI-Driven Software Development: Challenges and Lessons from the Field (Keynote) 2023 ·Eran Yahav	0
3	Neural Edit Completion. 2020 ·arXiv (Cornell University) ·Shaked Brody, Uri Alon, Eran Yahav	2
4	Neural Reverse Engineering of Stripped Binaries 2019 ·Yaniv David, Uri Alon, Eran Yahav	4
5	Programming by predicates: a formal model for interactive synthesis 2019 ·Acta Informatica ·Hila Peleg, Shachar Itzhaky, Sharon Shoham, Eran Yahav	1
6	Statistical Reconstruction of Class Hierarchies in Binaries 2018 ·(unknown), Noam Rinetzky, Eran Yahav	10
7	Extracting Automata from Recurrent Neural Networks Using Queries and Counterexamples 2017 ·International Conference on Machine Learning ·Gail Garfinkel Weiss, Yoav Goldberg, Eran Yahav	30
8	Programming with “Big Code” 2016 ·Martin Vechev, Eran Yahav	4
9	Code completion with statistical language models breakdown → 2014 ·Veselin Raychev, Martin Vechev, Eran Yahav	336
10	Verifying atomicity via data independence 2014 ·(unknown), Eran Yahav, Guy Golan Gueta, Alex Aiken, Nathan Bronson, Mooly Sagiv, Martin Vechev	9
11	Code completion with statistical language models 2014 ·ACM SIGPLAN Notices ·Veselin Raychev, Martin Vechev, Eran Yahav	132
12	Concurrent libraries with foresight 2013 ·ACM SIGPLAN Notices ·Guy Golan-Gueta, G. Ramalingam, Mooly Sagiv, Eran Yahav	3
13	Typestate-based semantic code search over partial programs 2012 ·(unknown), Sharon Shoham, Eran Yahav	69
14	Efficient data race detection for async-finish parallelism 2012 ·Formal Methods in System Design ·Raghavan Raman, Jisheng Zhao, Vivek Sarkar, Martin Vechev, Eran Yahav	10
15	Proceedings of the 18th international conference on Static analysis 2011 ·Eran Yahav	3
16	PHALANX 2010 ·Martin Vechev, Eran Yahav, Greta Yorsh	11
17	QVM 2008 ·Matthew Arnold, Martin Vechev, Eran Yahav	79
18	A survey of static analysis methods for identifying security vulnerabilities in software systems 2007 ·IBM Systems Journal ·Marco Pistoia, Satish Chandra, Stephen J. Fink, Eran Yahav	54
19	Effective typestate verification in the presence of aliasing 2006 ·Stephen J. Fink, Eran Yahav, Nurit Dor, G. Ramalingam, (unknown)	105
20	Typestate verification: Abstraction techniques and complexity results 2005 ·Science of Computer Programming ·John K. Field, (unknown), G. Ramalingam, Eran Yahav	7

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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