Paviththiren Sivasothilingam — accepted AI-conference papers

2025

Enhancing Autonomous Driving Systems with On-Board Deployed Large Language Models

Nicolas Baumann, Cheng Hu, Paviththiren Sivasothilingam, Haotong Qin, Lei Xie, Michele Magno +1

RSS 2025poster

Neural Networks (NNs) trained through supervised learning, struggle with managing edge-case scenarios common in real-world driving due to the intractability of exhaustive datasets covering all edge-cases, making knowledge-driven approaches, akin to how humans intuitively detect unexpected driving b…

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2025

RobotxR1: Enabling Embodied Robotic Intelligence on Large Language Models through Closed-Loop Reinforcement Learning

Liam Boyle, Nicolas Baumann, Paviththiren Sivasothilingam, Michele Magno, Luca Benini

CoRL 2025poster

Future robotic systems operating in real-world environments require on-board embodied intelligence without continuous cloud connection, balancing capabilities with constraints on computational power and memory. This work presents an extension of the R1-zero approach, which enables the usage of small…

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