Tactile-JEPA is an efficient self-supervised pre-training method that uses the spatial arrangement of tactile sensors to learn topology-aware representations, and is trained to predict the embeddings of masked sensing elements from the unmasked remainder, using the sensor connectivity graph to guide spatial masking.
E. Kovtun, M. Konovalov, Andrey Sakhovskiy et al.· 0 citations
Human-aligned chess models, designed to mimic human decision-making rather than maximize engine strength, pose a novel challenge for online fair-play enforcement. While prior work assesses these models on move prediction accuracy, their potential as sophisticated cheating tools and their utility for cheating detection...
Anastasiia Linich, A. Lepin, Andrey Sakhovskiy et al.· Proceedings of the 32nd ACM...· 0 citations
This work reveals that retrieval from a structured agent repository provides a cost-efficient, accurate, and controllable alternative to dynamic agent generation, responding to the strict demands of industrial applications.
Vitalii Belov, Artyom Sosedka, Andrey Sakhovskiy et al.· Annual International ACM SIG...· 0 citations
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