Alexander Nikulin

According to our database, Alexander Nikulin authored at least 24 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Vintix II: Decision Pre-Trained Transformer is a Scalable In-Context Reinforcement Learner.

Andrei Polubarov, Nikita Lyubaykin, Alexander Derevyagin, Artyom Grishin, Igor Saprygin, Aleksandr Serkov, Mark Averchenko, Daniil Tikhonov, Maksim Zhdanov, Alexander Nikulin, Ilya Zisman, Albina Klepach, Alexey Zemtsov, Vladislav Kurenkov

CoRR, April, 2026

Vision-Language Models Unlock Task-Centric Latent Actions.

Alexander Nikulin, Ilya Zisman, Albina Klepach, Denis Tarasov, Alexander Derevyagin, Andrei Polubarov, Nikita Lyubaykin, Vladislav Kurenkov

CoRR, January, 2026

Object-Centric Latent Action Learning.

Albina Klepach, Alexander Nikulin, Ilya Zisman, Denis Tarasov, Alexander Derevyagin, Andrei Polubarov, Nikita Lyubaykin, Igor Kiselev, Vladislav Kurenkov

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

NinA: Normalizing Flows in Action. Training VLA Models with Normalizing Flows.

Denis Tarasov, Alexander Nikulin, Ilya Zisman, Albina Klepach, Nikita Lyubaykin, Andrei Polubarov, Alexander Derevyagin, Vladislav Kurenkov

CoRR, August, 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, May, 2025

Zero-Shot Adaptation of Behavioral Foundation Models to Unseen Dynamics.

Maksim Bobrin, Ilya Zisman, Alexander Nikulin, Vladislav Kurenkov, Dmitry V. Dylov

CoRR, May, 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, February, 2025

Object-Centric Latent Action Learning.

Albina Klepach, Alexander Nikulin, Ilya Zisman, Denis Tarasov, Alexander Derevyagin, Andrei Polubarov, Nikita Lyubaykin, Vladislav Kurenkov

CoRR, February, 2025

Vintix: Action Model via In-Context Reinforcement Learning.

Andrei Polubarov, Nikita Lyubaykin, Alexander Derevyagin, Ilya Zisman, Denis Tarasov, Alexander Nikulin, Vladislav Kurenkov

Proceedings of the Forty-second International Conference on Machine Learning, 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

Proceedings of the Forty-second International Conference on Machine Learning, 2025

XLand-100B: A Large-Scale Multi-Task Dataset for In-Context Reinforcement Learning.

Alexander Nikulin, Ilya Zisman, Alexey Zemtsov, Vladislav Kurenkov

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

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, Viacheslav Sinii, Vladislav Kurenkov, Sergey Kolesnikov

CoRR, 2024

Open RL Benchmark: Comprehensive Tracked Experiments for Reinforcement Learning.

Shengyi Huang, Quentin Gallouédec, Florian Felten, Antonin Raffin, Rousslan Fernand Julien Dossa, Yanxiao Zhao, Ryan Sullivan, Viktor Makoviychuk, Denys Makoviichuk, Mohamad H. Danesh, Cyril Roumégous, Jiayi Weng, Chufan Chen, Md Masudur Rahman, João G. M. Araújo, Guorui Quan, Daniel Tan, Timo Klein, Rujikorn Charakorn, Mark Towers, Yann Berthelot, Kinal Mehta, Dipam Chakraborty, Arjun KG, Valentin Charraut, Chang Ye, Zichen Liu, Lucas N. Alegre, Alexander Nikulin, Xiao Hu, Tianlin Liu, Jongwook Choi, Brent Yi

CoRR, 2024

XLand-MiniGrid: Scalable Meta-Reinforcement Learning Environments in JAX.

Alexander Nikulin, Vladislav Kurenkov, Ilya Zisman, Artem Agarkov, Viacheslav Sinii, Sergey Kolesnikov

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Emergence of In-Context Reinforcement Learning from Noise Distillation.

Ilya Zisman, Vladislav Kurenkov, Alexander Nikulin, Viacheslav Sinii, Sergey Kolesnikov

Proceedings of the Forty-first International Conference on Machine Learning, 2024

In-Context Reinforcement Learning for Variable Action Spaces.

Viacheslav Sinii, Alexander Nikulin, Vladislav Kurenkov, Ilya Zisman, Sergey Kolesnikov

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

CORL: Research-oriented Deep Offline Reinforcement Learning Library.

Denis Tarasov, Alexander Nikulin, Dmitry Akimov, Vladislav Kurenkov, Sergey Kolesnikov

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Revisiting the Minimalist Approach to Offline Reinforcement Learning.

Denis Tarasov, Vladislav Kurenkov, Alexander Nikulin, Sergey Kolesnikov

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Katakomba: Tools and Benchmarks for Data-Driven NetHack.

Vladislav Kurenkov, Alexander Nikulin, Denis Tarasov, Sergey Kolesnikov

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Anti-Exploration by Random Network Distillation.

Alexander Nikulin, Vladislav Kurenkov, Denis Tarasov, Sergey Kolesnikov

Proceedings of the International Conference on Machine Learning, 2023

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

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

2021

MineRL Diamond 2021 Competition: Overview, Results, and Lessons Learned.

Anssi Kanervisto, Stephanie Milani, Karolis Ramanauskas, Nicholay Topin, Zichuan Lin, Junyou Li, Jianing Shi, Deheng Ye, Qiang Fu, Wei Yang, Weijun Hong, Zhongyue Huang, Haicheng Chen, Guangjun Zeng, Yue Lin, Vincent Micheli, Eloi Alonso, François Fleuret, Alexander Nikulin, Yury Belousov, Oleg Svidchenko, Aleksei Shpilman

Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track, 2021