AI2 Israel


The Allen Institute for AI Israel office was founded in 2019 in Sarona, Tel Aviv.

AI2's mission is to contribute to humanity through high-impact AI research and engineering.

AI2 Israel continues our mission of AI for the Common Good through groundbreaking research in natural language processing and machine learning, all in close association with the AI2 home office in Seattle, Washington.

The focus of AI2 Israel is bringing people closer to information, by creating and using advanced language-centered AI. As a scientific approach, we believe in combining strong linguistics-oriented foundations, state-of-the-art machine learning, and top-notch engineering, with a user oriented design. For application domains, we focus on understanding and answering complex questions, filling in commonsense gaps in text, and enabling robust extraction of structured information from text. This is an integral part of AI2’s vision of pushing the boundaries of the algorithmic understanding of human language and advancing the common good through AI.

AI2 Israel also enjoys research relationships with top local universities Tel Aviv University and Bar-Ilan University.


  • Yoav is the research director of AI2 Israel, and also an associate professor of computer science at Bar Ilan University. His research interests include language understanding technologies with real world applications, combining symbolic and neural representations, uncovering latent information in text, syntactic and semantic processing, and interpretability and foundational understanding of deep learning models for text and sequences. He authored a textbook on deep learning techniques for natural language processing, and was among the IEEE's AI Top 10 to Watch in 2018, and a recipient of the Krill Prize in Science in 2017. He received his Ph.D. in Computer Science from Ben Gurion University, and spent time in Google Research as a post-doc. Learn more

    Yoav Goldberg

  • Ron is the COO of AI2 Israel. He has vast experience in venture capital, entrepreneurship, and management with cutting edge technology organizations such as IDE technologies, Gilat, GVT, Scitex, Motorola and IAF. He is author of *The Imperfect Guide To Entrepreneurship*. He has an MBA from IMD, Switzerland and an MSc in Computer Science from TAU. He is happily married to Shlomit and the proud father of Dana and Gili, his best ever venture and seed investment. Learn more

    Ron Yachini

  • Jonathan Berant is a senior lecturer at The Blavatnik School of Computer Science in Tel-Aviv University, specializing in Natural Language Understanding. He holds a Ph.D in Computer Science from Tel-Aviv University, was a post-doctoral fellow at Stanford University from 2012-2015, and a post-doctoral fellow at Google Research from 2015-2016. Jonathan works on Natural Language Understanding problems such as Semantic Parsing, Question Answering, Paraphrasing, and Reading Comprehension. He is mostly excited about learning from weak supervision that is easy to obtain and grounded in the world. Learn more

    Jonathan Berant

  • Reut Tsarfaty is an Assistant Professor at the Computer Science Department at the Open University of Israel. Reut holds a BSc. from the Technion and MSc./PhD. from the Institute for Logic, Language and Computation (ILLC) at the University of Amsterdam. She also held postdoctoral research fellowships at Uppsala University in Sweden and at the Weizmann Institute in Israel. Her research focuses on Natural Language parsing, broadly interpreted to cover morphological, syntactic and semantic phenomena, in English and across typologically different languages. NLP applications she has worked on include (but are not limited to) natural language programming, natural language navigation, automated essay scoring, the analysis and generation of social media content, and more. Outside of work Reut practices being a mother, a partner, a female and a person, all at once. Some of her best friends are linguists and philosophers. Learn more

    Reut Tsarfaty

  • Hillel Taub-Tabib is a research engineer. Hillel holds an MA degree in linguistics from Tel-Aviv University and an MSc in computer science from the Hebrew University of Jerusalem. Prior to joining AI2 he led the NLP team at Melingo and the text analytics group at Basis Technology. In his free time he enjoys books, movies, chess and goofing around with his kids.

    Hillel Taub-Tabib

  • Micah Shlain is a software engineer working on relation extraction. He holds a B.S. in Computer Science and has more than a decade of experience in the software industry. Outside of work, he enjoys biking and reading books.

    Micah Shlain

  • Matan Eyal is a research engineer in AI2 Israel. Matan holds a B.S. in Computer Science and Statistics from Tel-Aviv University, and an MSc in Computer Science from Ben Gurion University. In his free time, he enjoys spending time with his family, sports and reading books.

    Matan Eyal

  • Yael was born and raised in Jerusalem. After graduating from high school she served as a sports instructor in the Israel Defense Forces. Yael recently moved to Tel Aviv to be part of the dynamic hi-tech scene. She is the office manager, in charge of day-to-day operations for the Israeli branch of AI2. When not working, Yael enjoys working out and taking long runs on the beach.

    Yael Rachmut


AI2 Israel is a non-profit offering exceptional opportunities for researchers and engineers to develop AI for the common good.

We are currently looking for outstanding software engineers and research engineers.
Candidates should send their CV to:


Recent publications from the AI2 Israel team.

  • Break It Down: A Question Understanding Benchmark TACL • 2020 Tomer Wolfson, Mor Geva, Ankit Gupta, Matt Gardner, Yoav Goldberg, Daniel Deutch, Jonathan Berant
    Understanding natural language questions entails the ability to break down a question into the requisite steps for computing its answer. In this work, we introduce a Question Decomposition Meaning Representation (QDMR) for questions. QDMR constitutes the ordered list of steps, expressed through…  (More)
  • Injecting Numerical Reasoning Skills into Language Models ACL • 2020 Mor Geva, Ankit Gupta, Jonathan Berant
    Large pre-trained language models (LMs) are known to encode substantial amounts of linguistic information. However, high-level reasoning skills, such as numerical reasoning, are difficult to learn from a language-modeling objective only. Consequently, existing models for numerical reasoning have…  (More)
  • Differentiable Scene Graphs WACV • 2020 Moshiko Raboh, Roei Herzig, Gal Chechik, Jonathan Berant, Amir Globerson
    Understanding the semantics of complex visual scenes involves perception of entities and reasoning about their relations. Scene graphs provide a natural representation for these tasks, by assigning labels to both entities (nodes) and relations (edges). However, scene graphs are not commonly used as…  (More)
  • oLMpics - On what Language Model Pre-training Captures arXiv • 2019 Alon Talmor, Yanai Elazar, Yoav Goldberg, Jonathan Berant
    Recent success of pre-trained language models (LMs) has spurred widespread interest in the language capabilities that they possess. However, efforts to understand whether LM representations are useful for symbolic reasoning tasks have been limited and scattered. In this work, we propose eight…  (More)
  • ORB: An Open Reading Benchmark for Comprehensive Evaluation of Machine Reading Comprehension EMNLP • MRQA Workshop • 2019 Dheeru Dua, Ananth Gottumukkala, Alon Talmor, Sameer Singh, Matt Gardner
    Reading comprehension is one of the crucial tasks for furthering research in natural language understanding. A lot of diverse reading comprehension datasets have recently been introduced to study various phenomena in natural language, ranging from simple paraphrase matching and entity typing to…  (More)
See All Papers from AI2 Israel
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