Yoav Artzi is an Assistant Professor in the Department of Computer Science and Cornell Tech at Cornell University. His research focuses on learning expressive models for natural language understanding, most recently in situated interactive scenarios. He received an NSF CAREER award, paper awards in EMNLP 2015, ACL 2017, and NAACL 2018, and Google faculty awards in 2015 and 2017. Yoav holds a B.Sc. summa cum laude from Tel Aviv University and a Ph.D. from the University of Washington.
Natural Language Processing
- "Situated Mapping of Sequential Instructions to Actions with Single-step Reward Observation" Alane Suhr and Yoav Artzi; In Proceedings of the Conference of the Association for Computational Linguistics (ACL), 2018.
- "Following High-level Navigation Instructions on a Simulated Quadcopter with Imitation Learning" Valts Blukis, Nataly Brukhim, Andrew Bennett, Ross A. Knepper, and Yoav Artzi; In Proceedings of the Robotics: Science and Systems Conference (RSS), 2018.
- "Learning to Map Context-Dependent Sentences to Executable Formal Queries" Alane Suhr, Srinivasan Iyer, and Yoav Artzi In Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2018.
- "A Dataset of 1.3 Million Summaries with Diverse Extractive Strategies" Max Grusky, Mor Naaman, and Yoav Artzi; In Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2018.
- "Mapping Instructions and Visual Observations to Actions with Reinforcement Learning" Dipendra Misra, John Langford, and Yoav Artzi; In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), 2017.
Selected Awards and Honors
- Outstanding Paper Award, NAACL, 2018
- NSF CAREER Award, 2018
- Google Faculty Research Award, 2015 and 2017
- Best Resource Paper Award, ACL, 2017
- Best Paper Award, EMNLP, 2015
- B.Sc. (Computer Science), Tel Aviv University, 2008
- Ph.D. (Computer Science and Engineering), University of Washington, 2015