133 citations · 510 across the 36 of their papers we have counts for
6 papers · 1 filter
Generative Negative Text Replay for Continual Vision-Language Pretraining
Shipeng Yan, Lanqing Hong, Hang Xu +4
Vision-language pre-training (VLP) has attracted increasing attention recently. With a large amount of image-text pairs, VLP models trained with contrastive loss have achieved impr…
DevNet: Self-supervised Monocular Depth Learning via Density Volume Construction
Kaichen Zhou, Lanqing Hong, Changhao Chen +4
Self-supervised depth learning from monocular images normally relies on the 2D pixel-wise photometric relation between temporally adjacent image frames. However, they neither fully…
CO^3: Cooperative Unsupervised 3D Representation Learning for Autonomous Driving
Runjian Chen, Yao Mu, Runsen Xu +5
Unsupervised contrastive learning for indoor-scene point clouds has achieved great successes. However, unsupervised learning point clouds in outdoor scenes remains challenging beca…
Self-Guided Noise-Free Data Generation for Efficient Zero-Shot Learning
Jiahui Gao, Renjie Pi, Yong Lin +7
There is a rising interest in further exploring the zero-shot learning potential of large pre-trained language models (PLMs). A new paradigm called data-generation-based zero-shot…
Revisiting Over-smoothing in BERT from the Perspective of Graph
Han Shi, Jiahui Gao, Hang Xu +5
Recently over-smoothing phenomenon of Transformer-based models is observed in both vision and language fields. However, no existing work has delved deeper to further investigate th…
ZeroGen: Efficient Zero-shot Learning via Dataset Generation
Jiacheng Ye, Jiahui Gao, Qintong Li +5
There is a growing interest in dataset generation recently due to the superior generative capacity of large pre-trained language models (PLMs). In this paper, we study a flexible a…