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Nicolas Sievers

2 accepted papers

2023

Practical Visual Deep Imitation Learning via Task-Level Domain Consistency

ICRA 2023poster

Recent work in visual end-to-end learning for robotics has shown the promise of imitation learning across a variety of tasks. Such approaches are however expensive both because they require large amounts of real world data and rely on time-consuming real-world evaluations to identify the best model…

Cited by 3SourceScholar
2022

Do As I Can, Not As I Say: Grounding Language in Robotic Affordances

CoRL 2022oral

Large language models can encode a wealth of semantic knowledge about the world. Such knowledge could be extremely useful to robots aiming to act upon high-level, temporally extended instructions expressed in natural language. However, a significant weakness of language models is that they lack real…

Cited by 1747SourcecodeScholar