Understanding the Effectiveness of Cross-Domain Contrastive Unsupervised Domain Adaptation. - Viacheslav Sinii; Adín Ramírez Rivera; Adil Khan 001 (Tiny Papers @ ICLR, 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)

The Differences Between Direct Alignment Algorithms are a Blur. - Alexey Gorbatovski; Boris Shaposhnikov; Viacheslav Sinii; Alexey Malakhov; Daniil Gavrilov (CoRR, 2025)

You Do Not Fully Utilize Transformer's Representation Capacity. - Gleb Gerasimov; Yaroslav Aksenov; Nikita Balagansky; Viacheslav Sinii; Daniil Gavrilov (CoRR, 2025)

Steering LLM Reasoning Through Bias-Only Adaptation. - Viacheslav Sinii; Alexey Gorbatovski; Artem Cherepanov; Boris Shaposhnikov; Nikita Balagansky; Daniil Gavrilov (CoRR, 2025)

ESSA: Evolutionary Strategies for Scalable Alignment. - Daria Korotyshova; Boris Shaposhnikov; Alexey Malakhov; Nikita Surnachev; George Bredis; Alexey Gorbatovski; Viacheslav Sinii; Daniil Gavrilov (CoRR, 2025)

Enhancing Vision-Language Model Training with Reinforcement Learning in Synthetic Worlds for Real-World Success. - George Bredis; Stanislav Dereka; Viacheslav Sinii; Ruslan Rakhimov; Daniil Gavrilov (CoRR, 2025)