An interactive robot pipeline that clarifies user intent, retrieves past corrected answers, and fine-tunes an MLLM on dialogue history improved accuracy on a 10-bottle medicine recognition task from 28.8% to 71.6%.
In: 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
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iLearnRobot: An Interactive Learning-Based Multi-Modal Robot with Continuous Improvement
An interactive robot pipeline that clarifies user intent, retrieves past corrected answers, and fine-tunes an MLLM on dialogue history improved accuracy on a 10-bottle medicine recognition task from 28.8% to 71.6%.