6 papers
Plan, Don't Pose: Long Composite Motion Generation with Text-Aligned BFM
Nikolay Shvetsov, Maksim Bobrin, Nazar Buzun +2
Text-to-motion (T2M) generation has broad applications in character animation, virtual avatars, and human-robot interaction. Existing methods typically generate pose trajectories o…
Zero-Shot Off-Policy Learning
Arip Asadulaev, Maksim Bobrin, Salem Lahlou +3
Off-policy learning methods seek to derive an optimal policy directly from a fixed dataset of prior interactions. This objective presents significant challenges, primarily due to t…
Convex Compositional Reasoning Models
Meir Roketlishvili, Semyon Semenov, Maksim Bobrin +7
Compositional energy-based models can generalize to larger combinatorial reasoning problems by reusing a learned factor energy across many local constraints. In our paper, we show…
Zero-Shot Adaptation of Behavioral Foundation Models to Unseen Dynamics
Maksim Bobrin, Ilya Zisman, Alexander Nikulin +2
Behavioral Foundation Models (BFMs) proved successful in producing policies for arbitrary tasks in a zero-shot manner, requiring no test-time training or task-specific fine-tuning.…
Random Direct Preference Optimization for Radiography Report Generation
Valentin Samokhin, Boris Shirokikh, Mikhail Goncharov +5
Radiography Report Generation (RRG) has gained significant attention in medical image analysis as a promising tool for alleviating the growing workload of radiologists. However, de…
ENOT: Expectile Regularization for Fast and Accurate Training of Neural Optimal Transport
Nazar Buzun, Maksim Bobrin, Dmitry V. Dylov
We present a new approach for Neural Optimal Transport (NOT) training procedure, capable of accurately and efficiently estimating optimal transportation plan via specific regulariz…