27 citations · 38 across the 11 of their papers we have counts for
12 papers
Designing for What Cannot Be Seen: Supporting Embodied String Learning for Musicians with Blindness and Low-Vision
Shi Shi, Lingyun Chen, Zitao Zhang +2
Bowed string instruments demand fine-grained bodily coordination that is typically taught through visual demonstration, creating persistent barriers for musicians with blindness an…
Positioning Modular Co-Design in Future HRI Design Research
Lingyun Chen, Qing Xiao, Zitao Zhang +2
Design-oriented HRI is increasingly interested in robots as long-term companions, yet many designs still assume a fixed form and a stable set of functions. We present an ongoing de…
Robots that Evolve with Us: Modular Co-Design for Personalization, Adaptability, and Sustainability
Lingyun Chen, Qing Xiao, Zitao Zhang +2
Many current robot designs prioritize efficiency and one-size-fits-all solutions, oftentimes overlooking personalization, adaptability, and sustainability. To explore alternatives,…
MLKV: Efficiently Scaling up Large Embedding Model Training with Disk-based Key-Value Storage
Yongjun He, Roger Waleffe, Zhichao Han +8
Many modern machine learning (ML) methods rely on embedding models to learn vector representations (embeddings) for a set of entities (embedding tables). As increasingly diverse ML…
BenchTemp: A General Benchmark for Evaluating Temporal Graph Neural Networks
Qiang Huang, Jiawei Jiang, Xi Susie Rao +10
To handle graphs in which features or connectivities are evolving over time, a series of temporal graph neural networks (TGNNs) have been proposed. Despite the success of these TGN…
Behavioral graph fraud detection in E-commerce
Hang Yin, Zitao Zhang, Zhurong Wang +5
In e-commerce industry, graph neural network methods are the new trends for transaction risk modeling.The power of graph algorithms lie in the capability to catch transaction linki…