Rokas Bendikas — accepted AI-conference papers

2025

Focusing on What Matters: Object-Agent-centric Tokenization for Vision Language Action models

Rokas Bendikas, Daniel Dijkman, Markus Peschl, Sanjay Haresh, Pietro Mazzaglia

CoRL 2025poster

Vision-Language-Action (VLA) models offer a pivotal approach to learning robotic manipulation at scale by repurposing large pre-trained Vision-Language-Models (VLM) to output robotic actions. However, adapting VLMs for robotic domains comes with an unnecessarily high computational cost, which we att…

Cited by 0 Source ↗Scholar ↗

2023

Learning Needle Pick-and-Place Without Expert Demonstrations

Rokas Bendikas, Valerio Modugno, Dimitrios Kanoulas, Francisco Vasconcelos, Danail Stoyanov

RA-L 2023

We introduce a novel approach for learning a complex multi-stage needle pick-and-place manipulation task for surgical applications using Reinforcement Learning without expert demonstrations or explicit curriculum. The proposed method is based on a recursive decomposition of the original task into a

Cited by 22 Source ↗Scholar ↗