E.T.-RNN: Applying Deep Learning to Credit Loan Applications. - Dmitrii Babaev; Maxim Savchenko; Alexander Tuzhilin; Dmitrii Umerenkov (KDD, 2019)

Event sequence metric learning. - Dmitrii Babaev; Ivan Kireev; Nikita Ovsov; Mariya Ivanova; Gleb Gusev; Alexander Tuzhilin (CoRR, 2020)

Insights From the NeurIPS 2021 NetHack Challenge. - Eric Hambro; Sharada P. Mohanty; Dmitrii Babaev; Minwoo Byeon; Dipam Chakraborty; Edward Grefenstette; Minqi Jiang; DaeJin Jo; Anssi Kanervisto; Jongmin Kim 006; Sungwoong Kim; Robert Kirk; et al. (NeurIPS (Competition and Demos), 2021)

Temporal Graph Network Embedding with Causal Anonymous Walks Representations. - Ilya Makarov; Andrey V. Savchenko; Arseny Korovko; Leonid Sherstyuk; Nikita Severin; Aleksandr Mikheev; Dmitrii Babaev (CoRR, 2021)

CoLES: Contrastive Learning for Event Sequences with Self-Supervision. - Dmitrii Babaev; Nikita Ovsov; Ivan Kireev; Mariya Ivanova; Gleb Gusev; Ivan Nazarov; Alexander Tuzhilin (SIGMOD Conference, 2022)

Temporal network embedding framework with causal anonymous walks representations. - Ilya Makarov; Andrey V. Savchenko; Arseny Korovko; Leonid Sherstyuk; Nikita Severin; Dmitrii Kiselev; Aleksandr Mikheev; Dmitrii Babaev (PeerJ Comput. Sci., 2022)

MERA Code: A Unified Framework for Evaluating Code Generation Across Tasks. - Artem Chervyakov; Alexander Kharitonov; Pavel Zadorozhny; Adamenko Pavel; Rodion Levichev; Dmitrii Vorobev; Dmitrii Salikhov; Aidar Valeev; Alena Pestova; Maria Dziuba; Ilseyar Alimova; Artem Zavgorodnev; et al. (CoRR, 2025)