most citedJacobian Norm for Unsupervised Source-Free Domain Adaptation

6 citations · 22 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL20223 cited

A Survey on Neural Abstractive Summarization Methods and Factual Consistency of Summarization

Meng Cao

Automatic summarization is the process of shortening a set of textual data computationally, to create a subset (a summary) that represents the most important pieces of information…

cs.LG20226 cited

Jacobian Norm for Unsupervised Source-Free Domain Adaptation

Weikai Li, Meng Cao, Songcan Chen

Unsupervised Source (data) Free domain adaptation (USFDA) aims to transfer knowledge from a well-trained source model to a related but unlabeled target domain. In such a scenario,…

cs.CV20225 cited

Unsupervised Pre-training for Temporal Action Localization Tasks

Can Zhang, Tianyu Yang, Junwu Weng +3

Unsupervised video representation learning has made remarkable achievements in recent years. However, most existing methods are designed and optimized for video classification. The…

cs.LG20222 cited

Synthetic Defect Generation for Display Front-of-Screen Quality Inspection: A Survey

Shancong Mou, Meng Cao, Zhendong Hong +3

Display front-of-screen (FOS) quality inspection is essential for the mass production of displays in the manufacturing process. However, the severe imbalanced data, especially the…

cs.LG20226 cited

Information Gain Propagation: a new way to Graph Active Learning with Soft Labels

Wentao Zhang, Yexin Wang, Zhenbang You +5

Graph Neural Networks (GNNs) have achieved great success in various tasks, but their performance highly relies on a large number of labeled nodes, which typically requires consider…

math.DS2014

Multiscale modelling couples patches of two-layer thin fluid flow

Meng Cao, A. J. Roberts

The multiscale gap-tooth scheme uses a given microscale simulator of complicated physical processes to enable macroscale simulations by computing only only small sparse patches. Th…