43 citations · 124 across the 14 of their papers we have counts for
Showing 2021Show all
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cs.LG2021★ 25 cited
Improving Multi-Modal Learning with Uni-Modal Teachers
Chenzhuang Du, Tingle Li, Yichen Liu +4
Learning multi-modal representations is an essential step towards real-world robotic applications, and various multi-modal fusion models have been developed for this purpose. Howev…
cs.LG2021
Intrinsically Motivated Self-supervised Learning in Reinforcement Learning
Yue Zhao, Chenzhuang Du, Hang Zhao +1
In vision-based reinforcement learning (RL) tasks, it is prevalent to assign auxiliary tasks with a surrogate self-supervised loss so as to obtain more semantic representations and…
cs.LG2021★ 43 cited
What Makes Multi-modal Learning Better than Single (Provably)
Yu Huang, Chenzhuang Du, Zihui Xue +3
The world provides us with data of multiple modalities. Intuitively, models fusing data from different modalities outperform their uni-modal counterparts, since more information is…