Natural Language Processing - Yoav Artzi - Cornell University
Explore a lecture on natural language instruction following for robotic control and collaboration. Dive into two projects that investigate learning to execute natural language commands with robotic agents and in collaborative scenarios. Discover new datasets, interpretable models, and learning methods combining supervised and reinforcement learning. Examine the task of mapping raw observations and language to low-level continuous control of a quadcopter drone, as well as the CerealBar multi-player 3D game for studying instruction following in collaborative environments. Learn about innovative approaches to natural language understanding in situated interactive scenarios, presented by Cornell University Assistant Professor Yoav Artzi. Gain insights into experimental setups, human evaluation, and cascaded evaluation metrics for assessing instruction following performance.