Task-Oriented Language Grounding for Language Input with Multiple Sub-Goals of Non-Linear Order. - Vladislav Kurenkov; Bulat Maksudov; Adil Khan 001 (CoRR, 2019)

Learning Stabilizing Control Policies for a Tensegrity Hopper with Augmented Random Search. - Vladislav Kurenkov; Hany Hamed; Sergei Savin (CoRR, 2020)

Guiding Evolutionary Strategies by Differentiable Robot Simulators. - Vladislav Kurenkov; Bulat Maksudov (CoRR, 2021)

Showing Your Offline Reinforcement Learning Work: Online Evaluation Budget Matters. - Vladislav Kurenkov; Sergey Kolesnikov (ICML, 2022)

Q-Ensemble for Offline RL: Don't Scale the Ensemble, Scale the Batch Size. - Alexander Nikulin; Vladislav Kurenkov; Denis Tarasov; Dmitry Akimov; Sergey Kolesnikov (CoRR, 2022)

Let Offline RL Flow: Training Conservative Agents in the Latent Space of Normalizing Flows. - Dmitriy Akimov; Vladislav Kurenkov; Alexander Nikulin; Denis Tarasov; Sergey Kolesnikov (CoRR, 2022)

Anti-Exploration by Random Network Distillation. - Alexander Nikulin; Vladislav Kurenkov; Denis Tarasov; Sergey Kolesnikov (ICML, 2023)

Katakomba: Tools and Benchmarks for Data-Driven NetHack. - Vladislav Kurenkov; Alexander Nikulin; Denis Tarasov; Sergey Kolesnikov (NeurIPS, 2023)

Revisiting the Minimalist Approach to Offline Reinforcement Learning. - Denis Tarasov; Vladislav Kurenkov; Alexander Nikulin; Sergey Kolesnikov (NeurIPS, 2023)

CORL: Research-oriented Deep Offline Reinforcement Learning Library. - Denis Tarasov; Alexander Nikulin; Dmitry Akimov; Vladislav Kurenkov; Sergey Kolesnikov (NeurIPS, 2023)

In-Context Reinforcement Learning for Variable Action Spaces. - Viacheslav Sinii; Alexander Nikulin; Vladislav Kurenkov; Ilya Zisman; Sergey Kolesnikov (ICML, 2024)

Emergence of In-Context Reinforcement Learning from Noise Distillation. - Ilya Zisman; Vladislav Kurenkov; Alexander Nikulin; Viacheslav Sinii; Sergey Kolesnikov (ICML, 2024)

XLand-MiniGrid: Scalable Meta-Reinforcement Learning Environments in JAX. - Alexander Nikulin; Vladislav Kurenkov; Ilya Zisman; Artem Agarkov; Viacheslav Sinii; Sergey Kolesnikov (NeurIPS, 2024)

XLand-100B: A Large-Scale Multi-Task Dataset for In-Context Reinforcement Learning. - Alexander Nikulin; Ilya Zisman; Alexey Zemtsov; Viacheslav Sinii; Vladislav Kurenkov; Sergey Kolesnikov (CoRR, 2024)

N-Gram Induction Heads for In-Context RL: Improving Stability and Reducing Data Needs. - Ilya Zisman; Alexander Nikulin; Andrei Polubarov; Nikita Lyubaykin; Vladislav Kurenkov (CoRR, 2024)

XLand-100B: A Large-Scale Multi-Task Dataset for In-Context Reinforcement Learning. - Alexander Nikulin; Ilya Zisman; Alexey Zemtsov; Vladislav Kurenkov (ICLR, 2025)

Vintix: Action Model via In-Context Reinforcement Learning. - Andrey Polubarov; Nikita Lyubaykin; Alexander Derevyagin; Ilya Zisman; Denis Tarasov; Alexander Nikulin; Vladislav Kurenkov (CoRR, 2025)

Latent Action Learning Requires Supervision in the Presence of Distractors. - Alexander Nikulin; Ilya Zisman; Denis Tarasov; Nikita Lyubaykin; Andrei Polubarov; Igor Kiselev; Vladislav Kurenkov (CoRR, 2025)

Object-Centric Latent Action Learning. - Albina Klepach; Alexander Nikulin; Ilya Zisman; Denis Tarasov; Alexander Derevyagin; Andrei Polubarov; Nikita Lyubaykin; Vladislav Kurenkov (CoRR, 2025)

Yes, Q-learning Helps Offline In-Context RL. - Denis Tarasov; Alexander Nikulin; Ilya Zisman; Albina Klepach; Andrei Polubarov; Nikita Lyubaykin; Alexander Derevyagin; Igor Kiselev; Vladislav Kurenkov (CoRR, 2025)

Zero-Shot Adaptation of Behavioral Foundation Models to Unseen Dynamics. - Maksim Bobrin; Ilya Zisman; Alexander Nikulin; Vladislav Kurenkov; Dmitry V. Dylov (CoRR, 2025)

Electrostatics from Laplacian Eigenbasis for Neural Network Interatomic Potentials. - Maksim Zhdanov 002; Vladislav Kurenkov (CoRR, 2025)

cadrille: Multi-modal CAD Reconstruction with Online Reinforcement Learning. - Maksim Kolodiazhnyi; Denis Tarasov; Dmitrii Zhemchuzhnikov; Alexander Nikulin; Ilya Zisman; Anna Vorontsova; Anton Konushin; Vladislav Kurenkov; Danila Rukhovich (CoRR, 2025)