Peer-Reviewed Publications and Conference Proceedings

  1. Dubova, M., Moskvichev, A., & Goldstone, R. (2020). Reinforcement Communication Learning in Different Social Network Structures. ICML 2020 1st Language and Reinforcement Learning Workshop

  2. Dubova, M., & Moskvichev, A. (2020). Effects of supervision, population size, and self-play on multi-agent reinforcement learning to communicate. Artificial Life Conference Proceedings (pp. 678-686).

  3. Dubova, M. & Goldstone, R. (2020). The Influences of Category Learning on Perceptual Reconstructions. (under review)

  4. Schweinsberg, M. et al. (2020). Same data, different conclusions: Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis. (under review)

  5. Ivanchei, I., Dubova, M. & Karpov, A. Computational Modeling of Categorization: a Review [In Russian]. (accepted to Russian Journal of Cognitive Science)

  6. Dubova, M. & Moskvichev, A. (2019). Adaptation Aftereffects as a Result of Bayesian Categorization. In Proceedings of the 41st Annual Meeting of the Cognitive Science Society (pp. 1669-1675).

  7. Belyy, A., Dubova, M. & Nekrasov, D. (2018). Improved Evaluation Framework for Complex Plagiarism Detection. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers) (Vol. 2, pp. 157-162).

  8. Belyy, A. & Dubova, M. (2018). Framework for Russian Plagiarism Detection Using Sentence Embedding Similarity and Negative Sampling. Computational Linguistics and Intellectual Technologies: papers from the Annual international conference “Dialogue” (pp. 96-109).

  9. Dubova, M. & Moskvichev, A. (2018). Illusions of Set as Categorical Perception [In Russian]. In Proceedings of Russian Conference on Cognitive Psychology (pp. 27-37). Russian Psychological Society

  10. Moskvichev, A., Dubova, M., Menshov, S. & Filchenkov, A. (2017). Using Linguistic Activity in Social Networks to Predict and Interpret Dark Psychological Traits. In Conference on Artificial Intelligence and Natural Language (pp. 16-26). Springer, Cham.