@inproceedings{b44d4342575e43a4a335741e8af29c35,
title = "DISCERN for Generalizable Robotic Contexts",
abstract = "This work demonstrates DISCERN (Detection Image System with Commonsense Efficient Ranking Network), a novel generalizable task-ranking approach to improve human-robot collaboration via {"}discern{"}-ing with commonsense knowledge (CSK) derived from huge data repositories, augmented with image models and other everyday premises. It is an explainable, efficient solution useful to dynamic multipurpose robots.",
keywords = "AI & Robotics, Commonsense Reasoning, CSK, Human-Robot Collaboration, Sustainable AI, Task Planning, XAI",
author = "Swagnik Roychoudhury and Varde, {Aparna S.}",
note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 2024 IEEE International Conference on Big Data, BigData 2024 ; Conference date: 15-12-2024 Through 18-12-2024",
year = "2024",
doi = "10.1109/BigData62323.2024.10826141",
language = "English",
series = "Proceedings - 2024 IEEE International Conference on Big Data, BigData 2024",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "8819--8821",
editor = "Wei Ding and Chang-Tien Lu and Fusheng Wang and Liping Di and Kesheng Wu and Jun Huan and Raghu Nambiar and Jundong Li and Filip Ilievski and Ricardo Baeza-Yates and Xiaohua Hu",
booktitle = "Proceedings - 2024 IEEE International Conference on Big Data, BigData 2024",
}