6 papers
Decoupled Early Exits for Task-Dependent Compute Allocation in Flow-Matching VLAs
Riccardo Andrea Izzo, Rimvydas Rubavicius, Gianluca Bardaro +3
Flow-matching Vision-Language-Action (VLA) models have emerged as a potential solution for generalist robot control, designed by combining a pretrained Vision-Language Model (VLM)…
Identifying Informative Environments for Cognition Parameter Inference via Bayesian Experimental Design
Manisha Dubey, Rimvydas Rubavicius, N. Siddharth +1
Computational cognitive modeling seeks to infer latent cognitive mechanisms underlying observed behavior. Bayesian inverse planning provides a principled framework for such inferen…
Towards Human Motion World Models via Executable Behaviour Representations
Rimvydas Rubavicius, Manisha Dubey, N. Siddharth +1
Human motion world models should capture motion's intentionality by being executable: adaptable to different actions and capable of assessing motion quality. To achieve this, we in…
Assistax: A Multi-Agent Hardware-Accelerated Reinforcement Learning Benchmark for Assistive Robotics
Leonard Hinckeldey, Elliot Fosong, Rimvydas Rubavicius +6
As embodied autonomous systems capable of assisting humans in daily activities remain a major goal for robotics, efficient and appropriate reinforcement learning (RL) simulation te…
Conversational Code Generation: a Case Study of Designing a Dialogue System for Generating Driving Scenarios for Testing Autonomous Vehicles
Rimvydas Rubavicius, Antonio Valerio Miceli-Barone, Alex Lascarides +1
Cyber-physical systems like autonomous vehicles are tested in simulation before deployment, using domain-specific programs for scenario specification. To aid the testing of autonom…
SECURE: Semantics-aware Embodied Conversation under Unawareness for Lifelong Robot Learning
Rimvydas Rubavicius, Peter David Fagan, Alex Lascarides +1
This paper addresses a challenging interactive task learning scenario we call rearrangement under unawareness: an agent must manipulate a rigid-body environment without knowing a k…