Carl Yang
7 papers in the PaperMetrix corpus
Papers by this author
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Relationship Profiling over Social Networks: Reverse Smoothness from Similarity to Closeness
2017 · arXiv (Cornell University)
On social networks, while nodes bear rich attributes, we often lack the `semantics' of why each link is formed-- and thus we are missing the `road signs' to navigate and organize the complex social universe. …
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Neighborhood-Regularized Self-Training for Learning with Few Labels
2023 · arXiv (Cornell University)
Training deep neural networks (DNNs) with limited supervision has been a popular research topic as it can significantly alleviate the annotation burden. Self-training has been successfully applied in semi-supervised learning tasks, but one drawback of …
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A Review on Knowledge Graphs for Healthcare: Resources, Applications, and Promises
2023 · arXiv (Cornell University)
This comprehensive review aims to provide an overview of the current state of Healthcare Knowledge Graphs (HKGs), including their construction, utilization models, and applications across various healthcare and biomedical research domains. We thoroughly analyzed existing …
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Deep Efficient Private Neighbor Generation for Subgraph Federated Learning
2024 · Society for Industrial and Applied Mathematics eBooks
Behemoth graphs are often fragmented and separately stored by multiple data owners as distributed subgraphs in many realistic applications. Without harming data privacy, it is natural to consider the subgraph federated learning (subgraph FL) scenario, …
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SimRAG: Self-Improving Retrieval-Augmented Generation for Adapting Large Language Models to Specialized Domains
2025
Ran Xu, Hui Liu, Sreyashi Nag, Zhenwei Dai, Yaochen Xie, Xianfeng Tang, Chen Luo, Yang Li, Joyce C. Ho, Carl Yang, Qi He. Proceedings of the 2025 Conference of the Nations of the Americas Chapter …
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Beyond Memorization: A Rigorous Evaluation Framework for Medical Knowledge Editing
2025 · arXiv (Cornell University)
Recently, knowledge editing (KE) has emerged as a promising approach to update specific facts in Large Language Models (LLMs) without the need for full retraining. Despite the effectiveness in general-domain benchmarks, their applicability to complex …
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Transferable Graph Condensation from the Causal Perspective
2026 · Proceedings of the AAAI Conference on Artificial Intelligence
The increasing scale of graph datasets has significantly improved the performance of graph representation learning methods, but it has also introduced substantial training challenges. Graph dataset condensation techniques have emerged to compress large datasets into …