Haoteng Yin

According to our database, Haoteng Yin authored at least 18 papers between 2017 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

Differentially Private Relational Learning with Entity-level Privacy Guarantees.

Yinan Huang, Haoteng Yin, Eli Chien, Rongzhe Wei, Pan Li

CoRR, June, 2025

Do LLMs Really Forget? Evaluating Unlearning with Knowledge Correlation and Confidence Awareness.

Rongzhe Wei, Peizhi Niu, Hans Hao-Hsun Hsu, Ruihan Wu, Haoteng Yin, Mohsen Ghassemi, Yifan Li, Vamsi K. Potluru, Eli Chien, Kamalika Chaudhuri, Olgica Milenkovic, Pan Li

CoRR, June, 2025

How to Talk to Language Models: Serialization Strategies for Structured Entity Matching.

Haoteng Yin, Jinha Kim, Prashant Mathur, Krishanu Sarker, Vidit Bansal

Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2025, Albuquerque, New Mexico, USA, April 29, 2025

2024

On the Inherent Privacy Properties of Discrete Denoising Diffusion Models.

Rongzhe Wei, Eleonora Kreacic, Haoyu Peter Wang, Haoteng Yin, Eli Chien, Vamsi K. Potluru, Pan Li

Trans. Mach. Learn. Res., 2024

Privately Learning from Graphs with Applications in Fine-tuning Large Language Models.

Haoteng Yin, Rongzhe Wei, Eli Chien, Pan Li

CoRR, 2024

Learning Scalable Structural Representations for Link Prediction with Bloom Signatures.

Tianyi Zhang, Haoteng Yin, Rongzhe Wei, Pan Li, Anshumali Shrivastava

Proceedings of the ACM on Web Conference 2024, 2024

SocialCVAE: Predicting Pedestrian Trajectory via Interaction Conditioned Latents.

Wei Xiang, Haoteng Yin, He Wang, Xiaogang Jin

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

SUREL+: Moving from Walks to Sets for Scalable Subgraph-based Graph Representation Learning.

Haoteng Yin, Muhan Zhang, Jianguo Wang, Pan Li

Proc. VLDB Endow., 2023

On the Inherent Privacy Properties of Discrete Denoising Diffusion Models.

Rongzhe Wei, Eleonora Kreacic, Haoyu Wang, Haoteng Yin, Eli Chien, Vamsi K. Potluru, Pan Li

CoRR, 2023

OCTAL: Graph Representation Learning for LTL Model Checking.

Prasita Mukherjee, Haoteng Yin

CoRR, 2023

2022

Algorithm and System Co-design for Efficient Subgraph-based Graph Representation Learning.

Haoteng Yin, Muhan Zhang, Yanbang Wang, Jianguo Wang, Pan Li

Proc. VLDB Endow., 2022

OCTAL: Graph Representation Learning for LTL Model Checking.

Prasita Mukherjee, Haoteng Yin, Susheel Suresh, Tiark Rompf

CoRR, 2022

Understanding Non-linearity in Graph Neural Networks from the Bayesian-Inference Perspective.

Rongzhe Wei, Haoteng Yin, Junteng Jia, Austin R. Benson, Pan Li

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks.

Haorui Wang, Haoteng Yin, Muhan Zhang, Pan Li

Proceedings of the Tenth International Conference on Learning Representations, 2022

2020

Revisit graph neural networks and distance encoding in a practical view.

Haoteng Yin, Yanbang Wang, Pan Li

CoRR, 2020

2019

ST-UNet: A Spatio-Temporal U-Network for Graph-structured Time Series Modeling.

Bing Yu, Haoteng Yin, Zhanxing Zhu

CoRR, 2019

2018

Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting.

Bing Yu, Haoteng Yin, Zhanxing Zhu

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

2017

Spatio-temporal Graph Convolutional Neural Network: A Deep Learning Framework for Traffic Forecasting.

Bing Yu, Haoteng Yin, Zhanxing Zhu

CoRR, 2017