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20212026
most citedTask-customized Masked AutoEncoder via Mixture of Cluster-conditional Experts

6 citations · 14 across the 7 of their papers we have counts for

collaborators

8 papers

cs.SD2026

KunSet: A Corpus and Benchmark for Lyrics Alignment and Rhyme Retrieval in Kunqu Opera

Lejun Min, Siqi Chen, Delong Wang +10

Kunqu is one of the oldest extant forms of Chinese opera, yet its digitization remains scarce and difficult to annotate, with two challenges standing out: first, close analysis of…

cs.CL2025★ 2 cited

Automated Construction of a Knowledge Graph of Nuclear Fusion Energy for Effective Elicitation and Retrieval of Information

Andrea Loreti, Kesi Chen, Ruby George +3

In this document, we discuss a multi-step approach to automated construction of a knowledge graph, for structuring and representing domain-specific knowledge from large document co…

cs.CV2024★ 6 cited

Task-customized Masked AutoEncoder via Mixture of Cluster-conditional Experts

Zhili Liu, Kai Chen, Jianhua Han +4

Masked Autoencoder~(MAE) is a prevailing self-supervised learning method that achieves promising results in model pre-training. However, when the various downstream tasks have data…

cs.LG2023

Adversarial Erasing with Pruned Elements: Towards Better Graph Lottery Ticket

Yuwen Wang, Shunyu Liu, Kaixuan Chen +5

Graph Lottery Ticket (GLT), a combination of core subgraph and sparse subnetwork, has been proposed to mitigate the computational cost of deep Graph Neural Networks (GNNs) on large…

cs.CV2023★ 2 cited

GeoDiffusion: Text-Prompted Geometric Control for Object Detection Data Generation

Kai Chen, Enze Xie, Zhe Chen +4

Diffusion models have attracted significant attention due to the remarkable ability to create content and generate data for tasks like image classification. However, the usage of d…

cs.CV2023★ 1 cited

Mixed Autoencoder for Self-supervised Visual Representation Learning

Kai Chen, Zhili Liu, Lanqing Hong +3

Masked Autoencoder (MAE) has demonstrated superior performance on various vision tasks via randomly masking image patches and reconstruction. However, effective data augmentation s…

cs.AI2022★ 1 cited

Urban Region Profiling via A Multi-Graph Representation Learning Framework

Y. Luo, F. Chung, K. Chen

Urban region profiling can benefit urban analytics. Although existing studies have made great efforts to learn urban region representation from multi-source urban data, there are s…

cs.CV2021★ 2 cited

MultiSiam: Self-supervised Multi-instance Siamese Representation Learning for Autonomous Driving

Kai Chen, Lanqing Hong, Hang Xu +2

Autonomous driving has attracted much attention over the years but turns out to be harder than expected, probably due to the difficulty of labeled data collection for model trainin…