ImageNet Classification with Deep Convolutional Neural Networks
A deep convolutional network demonstrated how data, GPU computation and learned representations could transform visual recognition.
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FACT: A Multimodal Force-Action-Track Foundation Model for Human-to-Robot Dexterity
Human and robot demonstrations are combined with force-aware planning for dexterous manipulation.
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Why read this
A recent preprint: examine the task setup, force supervision and limits of cross-embodiment transfer.
Citation
@misc{cao2026fact,
title = {FACT: A Multimodal Force-Action-Track Foundation Model for Human-to-Robot Dexterity},
author = {Zhi Cao and Yining Hong and Jiaolong Yang and Yejin Choi and Li Fei-Fei and Jiajun Wu and Huang Huang},
year = {2026},
eprint = {2610.19155},
archivePrefix = {arXiv},
primaryClass = {cs.RO},
url = {https://arxiv.org/abs/2610.19155}
}Rights remain with the original authors. Refer to the original source for citations and licensing.
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