26 citations · 58 across the 12 of their papers we have counts for
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cs.LG2022
SHAPE: An Unified Approach to Evaluate the Contribution and Cooperation of Individual Modalities
Pengbo Hu, Xingyu Li, Yi Zhou
As deep learning advances, there is an ever-growing demand for models capable of synthesizing information from multi-modal resources to address the complex tasks raised from real-l…
cs.LG2022★ 2 cited
Adversarial Fine-tune with Dynamically Regulated Adversary
Pengyue Hou, Ming Zhou, Jie Han +2
Adversarial training is an effective method to boost model robustness to malicious, adversarial attacks. However, such improvement in model robustness often leads to a significant…
cs.LG2020★ 26 cited
Learning with Instance-Dependent Label Noise: A Sample Sieve Approach
Hao Cheng, Zhaowei Zhu, Xingyu Li +3
Human-annotated labels are often prone to noise, and the presence of such noise will degrade the performance of the resulting deep neural network (DNN) models. Much of the literatu…