5 papers · 1 filter
When Plans Change, Remember: Replanning-Guided Visual Memory for Vision-Language-Action Models
Victoria Smelova, Daniil Kazachkov, Georgiy Kazantsev +6
Long-horizon, multi-stage Vision-Language-Action (VLA) policies often require visual information that is no longer present in the current observation. Retaining the complete observ…
MIKASA-Robo-VLA: Benchmarking Memory in VLA Models for Long-Horizon Manipulation
Egor Cherepanov, Nikita Kachaev, Aleksandr I. Panov +1
Vision-language-action policies often see only one or a few recent frames, which makes it difficult to evaluate how they use information that disappears during a task. We introduce…
VLA Grounder: Language-Conditioning Space Optimization for Black-Box VLA Models
Damir Shodiev, Aleksei Staroverov, Nikita Kachaev +2
Vision-Language-Action (VLA) models are commonly treated as end-to-end action policies conditioned on natural-language task descriptions. In practice, however, their behavior often…
Does VLA Even Know the Basics? Measuring Commonsense and World Knowledge Retention in Vision-Language-Action Models
Nikita Kachaev, Andrey Moskalenko, Matvey Skripkin +10
Embodied Vision-Language-Action (VLA) models are typically obtained by fine-tuning powerful pretrained VLMs on robotics data, yet it is unclear how much commonsense and factual kno…
VLA: On Recurrent Memory for Partially Observable Manipulation in VLA Models
Egor Cherepanov, Nikita Kachaev, Daniil Zelezetsky +6
Vision-language-action (VLA) models predict chunks of future actions from the current observation, an assumption that fails under partial observability, where decisions depend on i…