Canada CIFAR AI Chair
Pan-Canadian AI Strategy
Vered Shwartz is is a Canada CIFAR AI Chair at the Vector Institute. She is an Assistant Professor of Computer Science at the University of British Columbia. Previously, she was a postdoctoral researcher at the Allen Institute for AI (AI2) and the University of Washington.
Shwartz’s research focuses on natural language processing, with the fundamental goal of building models capable of human-level understanding of natural language. Her research involves different problems in computational semantics and pragmatics, and commonsense reasoning. In particular, she is working on learning to uncover implicit meaning (“reading between the lines”), which is abundant in human speech, and on developing machines with advanced reasoning skills.
- AI2 Research Gift, The Allen Institute for AI (AI2), 2021
- The Eric and Wendy Schmidt Postdoctoral Award for Women in Mathematical and Computing Sciences, The Schmidt Family Foundation, 2019
- AI2 Key Scientific Challenges Program, The Allen Institute for AI (AI2), 2017
- Clore Foundation Scholarship for Excellent Ph.D. Students, Clore Israel Foundation, 2017
- Vered Shwartz, Yoav Goldberg, Ido Dagan. (2016). Improving Hypernymy Detection with an Integrated Path-based and Distributional Method. In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 2389–2398, Berlin, Germany. Association for Computational Linguistics. (Outstanding paper award).
- Vered Shwartz, Ido Dagan. (2019). Still a Pain in the Neck: Evaluating Text Representations on Lexical Composition. Transactions of the Association for Computational Linguistics; 7 403–419. doi: https://doi.org/10.1162/tacl_a_00277
- Shany Barhom, Vered Shwartz, Alon Eirew, Michael Bugert, Nils Reimers, Ido Dagan. (2019). Revisiting Joint Modeling of Cross-document Entity and Event Coreference Resolution. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 4179–4189, Florence, Italy. Association for Computational Linguistics.
- Vered Shwartz, Peter West, Ronan Le Bras, Chandra Bhagavatula, Yejin Choi. (2020). Unsupervised Commonsense Question Answering with Self-Talk. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 4615–4629, Online. Association for Computational Linguistics.
- Qin, L., Shwartz, V., West, P., Bhagavatula, C., Hwang, J.D., Le Bras, R., Bosselut, A., & Choi, Y. (2020). Back to the Future: Unsupervised Backprop-based Decoding for Counterfactual and Abductive Commonsense Reasoning. ArXiv, abs/2010.05906.
CIFAR is a registered charitable organization supported by the governments of Canada, Alberta and Quebec, as well as foundations, individuals, corporations and Canadian and international partner organizations.