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SUMMARY:CS & LCSR Seminar Series: Language-Driven Learning for Interactive Robotics
DESCRIPTION:Abstract\nBuilding and deploying broadly capable robots requires systems that can efficiently learn from and work with people. To achieve this\, robots must balance capability—the fundamental tools necessary to enable real-world deployment—and sustainability—the ability to grow and adapt through human feedback. In this talk\, Siddharth Karamcheti will motivate language-driven learning to tackle these axes\, providing robots with better abstractions for perception\, action\, and human-robot interaction. Towards capability\, he will present Voltron\, his approach for using language to learn visual representations that can be efficiently adapted for diverse robotics tasks. Building on these ideas\, he will discuss Prismatic\, his experimental framework for developing visually conditioned language models and vision-language-action policies at scale. Towards sustainability\, Karamcheti will next introduce Vocal Sandbox\, a new framework that integrates these models to develop collaborative robots that can work alongside human partners\, using language to express uncertainty and learn new behaviors from real-time interactions. Finally\, he will conclude with open challenges for enhancing both the capability and sustainability of modern robots\, with directions for future work. \nSpeaker Biography\nSiddharth Karamcheti is a final-year PhD student at Stanford University advised by Dorsa Sadigh and Percy Liang\, and a robotics intern at the Toyota Research Institute. His research focuses on robot learning\, natural language processing\, and human-robot interaction\, with the goal of developing scalable approaches for human-robot collaboration. Prior to his PhD\, Karamcheti earned his bachelor’s degree in computer science and literary arts at Brown University\, where he worked with Eugene Charniak and Stefanie Tellex. He is a recipient of a 2018 Open Philanthropy AI Fellowship\, is a 2024 Robotics: Science and Systems (RSS) Pioneer\, and his research has won paper awards at conferences such as RSS\, the Conference on Robot Learning\, the IEEE International Conference on Robotics and Automation\, and the Meeting of the Association for Computational Linguistics. \nZoom link >>
URL:https://www.cs.jhu.edu/event/cs-lcsr-seminar-series-language-driven-learning-for-interactive-robotics/
LOCATION:B-17 Hackerman Hall
CATEGORIES:Seminars and Lectures
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