| 2026 | KDD | UniLLM: A Unified Large Language Model for Multi?Modal Urban Dynamics Prediction. | Yuhang Liu, Yingxue Zhang, Xin Zhang, Yanhua Li, Jun Luo |
| 2025 | AISTATS | InnerThoughts: Disentangling Representations and Predictions in Large Language Models. | Didier Chtelat, Joseph Cotnareanu, Rylee Thompson, Yingxue Zhang, Mark Coates |
| 2025 | ASPDAC | MTLSO: A Multi-Task Learning Approach for Logic Synthesis Optimization. | Faezeh Faez, Raika Karimi, Yingxue Zhang, Xing Li, Lei Chen, Mingxuan Yuan, Mahdi Biparva |
| 2025 | EMNLP | Retrieval-Augmented Machine Translation with Unstructured Knowledge. | Jiaan Wang, Fandong Meng, Yingxue Zhang, Jie Zhou |
| 2025 | ICDM | MARCEL: Multifaceted SpAtial-TempoRal ContrastivE Learning for Generic Spatial-Temporal Representations. | Yuhang Liu, Yingxue Zhang, Xin Zhang, Yu Yang, Yanhua Li, Jun Luo |
| 2025 | IJCAI | The Graph's Apprentice: Teaching an LLM Low-Level Knowledge for Circuit Quality Estimation. | Reza Moravej, Saurabh Bodhe, Zhanguang Zhang, Didier Chtelat, Dimitrios Tsaras, Yingxue Zhang, Hui-Ling Zhen, Jianye Hao, Mingxuan Yuan |
| 2025 | IROS | ET-Plan-Bench: Embodied Task-level Planning Benchmark Towards Spatial-Temporal Cognition with Foundation Models. | Lingfeng Zhang, Yuening Wang, Hongjian Gu, Atia Hamidizadeh, Zhanguang Zhang, Yuecheng Liu, Yutong Wang, David Gamaliel Arcos Bravo, Junyi Dong, Shunbo Zhou, Tongtong Cao, Xingyue Quan, Yuzheng Zhuang, Yingxue Zhang, Jianye Hao |
| 2025 | KDD | UrbanMind: Urban Dynamics Prediction with Multifaceted Spatial-Temporal Large Language Models. | Yuhang Liu, Yingxue Zhang, Xin Zhang, Ling Tian, Yanhua Li, Jun Luo |
| 2025 | KDD | TransPlace: Transferable Circuit Global Placement via Graph Neural Network. | Yunbo Hou, Haoran Ye, Shuwen Yang, Yingxue Zhang, Siyuan Xu, Guojie Song |
| 2024 | ACL | EWEK-QA : Enhanced Web and Efficient Knowledge Graph Retrieval for Citation-based Question Answering Systems. | Mohammad Dehghan, Mohammad Ali Alomrani, Sunyam Bagga, David Alfonso-Hermelo, Khalil Bibi, Abbas Ghaddar, Yingxue Zhang, Xiaoguang Li, Jianye Hao, Qun Liu, Jimmy Lin, Boxing Chen, Prasanna Parthasarathi, Mahdi Biparva, Mehdi Rezagholizadeh |
| 2024 | AISTATS | Multi-resolution Time-Series Transformer for Long-term Forecasting. | Yitian Zhang, Liheng Ma, Soumyasundar Pal, Yingxue Zhang, Mark Coates |
| 2024 | CIKM | Enhancing Click-through Rate Prediction in Recommendation Domain with Search Query Representation. | Yuening Wang, Man Chen, Yaochen Hu, Wei Guo, Yingxue Zhang, Huifeng Guo, Yong Liu, Mark Coates |
| 2024 | ICDM | Align Along Time and Space: A Graph Latent Diffusion Model for Traffic Dynamics Prediction. | Yuhang Liu, Yingxue Zhang, Xin Zhang, Yu Yang, Yiqun Xie, Sahar Ghanipoor Machiani, Yanhua Li, Jun Luo |
| 2024 | ICML | CKGConv: General Graph Convolution with Continuous Kernels. | Liheng Ma, Soumyasundar Pal, Yitian Zhang, Jiaming Zhou, Yingxue Zhang, Mark Coates |
| 2024 | KDD | RoutePlacer: An End-to-End Routability-Aware Placer with Graph Neural Network. | Yunbo Hou, Haoran Ye, Yingxue Zhang, Siyuan Xu, Guojie Song |
| 2024 | KDD | GraSS: Combining Graph Neural Networks with Expert Knowledge for SAT Solver Selection. | Zhanguang Zhang, Didier Chtelat, Joseph Cotnareanu, Amur Ghose, Wenyi Xiao, Hui-Ling Zhen, Yingxue Zhang, Jianye Hao, Mark Coates, Mingxuan Yuan |
| 2024 | KDD | Urban-Focused Multi-Task Offline Reinforcement Learning with Contrastive Data Sharing. | Xinbo Zhao, Yingxue Zhang, Xin Zhang, Yu Yang, Yiqun Xie, Yanhua Li, Jun Luo |
| 2024 | VCIP | Cross-Device Image Saliency Detection: Database and Comparative Analysis. | Xiaoying Ding, Guanghui Yue, Yingxue Zhang |
| 2023 | AAAI | Neighbor Auto-Grouping Graph Neural Networks for Handover Parameter Configuration in Cellular Network. | Mehrtash Mehrabi, Walid Masoudimansour, Yingxue Zhang, Jie Chuai, Zhitang Chen, Mark Coates, Jianye Hao, Yanhui Geng |
| 2023 | AAAI | Structure Aware Incremental Learning with Personalized Imitation Weights for Recommender Systems. | Yuening Wang, Yingxue Zhang, Antonios Valkanas, Ruiming Tang, Chen Ma, Jianye Hao, Mark Coates |
| 2023 | AISTATS | Spectral Augmentations for Graph Contrastive Learning. | Amur Ghose, Yingxue Zhang, Jianye Hao, Mark Coates |
| 2023 | CIKM | Dynamic Embedding Size Search with Minimum Regret for Streaming Recommender System. | Bowei He, Xu He, Renrui Zhang, Yingxue Zhang, Ruiming Tang, Chen Ma |
| 2023 | CIKM | Dual-Process Graph Neural Network for Diversified Recommendation. | Yuanyi Ren, Hang Ni, Yingxue Zhang, Xi Wang, Guojie Song, Dong Li, Jianye Hao |
| 2023 | ICDE | Intent-aware Multi-source Contrastive Alignment for Tag-enhanced Recommendation. | Haolun Wu, Yingxue Zhang, Chen Ma, Wei Guo, Ruiming Tang, Xue Liu, Mark Coates |
| 2023 | ICML | Bidirectional Learning for Offline Model-based Biological Sequence Design. | Can Chen, Yingxue Zhang, Xue Liu, Mark Coates |
| 2023 | IJCAI | A Survey on User Behavior Modeling in Recommender Systems. | Zhicheng He, Weiwen Liu, Wei Guo, Jiarui Qin, Yingxue Zhang, Yaochen Hu, Ruiming Tang |
| 2023 | KDD | Hierarchical Projection Enhanced Multi-behavior Recommendation. | Chang Meng, Hengyu Zhang, Wei Guo, Huifeng Guo, Haotian Liu, Yingxue Zhang, Hongkun Zheng, Ruiming Tang, Xiu Li, Rui Zhang |
| 2023 | WWW | Compressed Interaction Graph based Framework for Multi-behavior Recommendation. | Wei Guo, Chang Meng, Enming Yuan, Zhicheng He, Huifeng Guo, Yingxue Zhang, Bo Chen, Yaochen Hu, Ruiming Tang, Xiu Li, Rui Zhang |
| 2023 | WWW | Dynamically Expandable Graph Convolution for Streaming Recommendation. | Bowei He, Xu He, Yingxue Zhang, Ruiming Tang, Chen Ma |
| 2023 | VCIP | A Lightweight No-reference Video Quality Assessment Method. | Huiying Shi, Yaosi Hu, Yingxue Zhang, Zhenzhong Chen |
| 2023 | SDM | STM-GAIL: Spatial-Temporal Meta-GAIL for Learning Diverse Human Driving Strategies. | Yingxue Zhang, Yanhua Li, Xun Zhou, Ziming Zhang, Jun Luo |
| 2022 | CIKM | OptEmbed: Learning Optimal Embedding Table for Click-through Rate Prediction. | Fuyuan Lyu, Xing Tang, Hong Zhu, Huifeng Guo, Yingxue Zhang, Ruiming Tang, Xue Liu |
| 2022 | CIKM | Adapting Triplet Importance of Implicit Feedback for Personalized Recommendation. | Haolun Wu, Chen Ma, Yingxue Zhang, Xue Liu, Ruiming Tang, Mark Coates |
| 2022 | EMNLP | WeTS: A Benchmark for Translation Suggestion. | Zhen Yang, Fandong Meng, Yingxue Zhang, Ernan Li, Jie Zhou |
| 2022 | ICASSP | Dual Path Graph Convolutional Networks. | Yunhe Li, Yaochen Hu, Yingxue Zhang |
| 2022 | ICDM | Mest-GAN: Cross-City Urban Traffic Estimation with Me ta S patial-T emporal G enerative A dversarial N etworks. | Yingxue Zhang, Yanhua Li, Xun Zhou, Jun Luo |
| 2022 | ICDM | STrans-GAN: Spatially-Transferable Generative Adversarial Networks for Urban Traffic Estimation. | Yingxue Zhang, Yanhua Li, Xun Zhou, Xiangnan Kong, Jun Luo |
| 2022 | ICDM | Invariant Factor Graph Neural Networks. | Zheng Fang, Ziyun Zhang, Guojie Song, Yingxue Zhang, Dong Li, Jianye Hao, Xi Wang |
| 2022 | KDD | Learning Binarized Graph Representations with Multi-faceted Quantization Reinforcement for Top-K Recommendation. | Yankai Chen, Huifeng Guo, Yingxue Zhang, Chen Ma, Ruiming Tang, Jingjie Li, Irwin King |
| 2022 | KDD | Generalizable Floorplanner through Corner Block List Representation and Hypergraph Embedding. | Mohammad Amini, Zhanguang Zhang, Surya Penmetsa, Yingxue Zhang, Jianye Hao, Wulong Liu |
| 2022 | WWW | Polarized Graph Neural Networks. | Zheng Fang, Lingjun Xu, Guojie Song, Qingqing Long, Yingxue Zhang |
| 2022 | SIGIR | EFLEC: Efficient Feature-LEakage Correction in GNN based Recommendation Systems. | Ishaan Kumar, Yaochen Hu, Yingxue Zhang |
| 2022 | VCIP | Video Quality Assessment based on Quality Aggregation Networks. | Wei Wo, Yingxue Zhang, Yaosi Hu, Zhenzhong Chen, Shan Liu |
| 2022 | WSDM | Modeling Scale-free Graphs with Hyperbolic Geometry for Knowledge-aware Recommendation. | Yankai Chen, Menglin Yang, Yingxue Zhang, Mengchen Zhao, Ziqiao Meng, Jianye Hao, Irwin King |
| 2021 | AAAI | Knowledge-Enhanced Top-K Recommendation in Poincar Ball. | Chen Ma, Liheng Ma, Yingxue Zhang, Haolun Wu, Xue Liu, Mark Coates |
| 2021 | AISTATS | Detection and Defense of Topological Adversarial Attacks on Graphs. | Yingxue Zhang, Florence Regol, Soumyasundar Pal, Sakif Khan, Liheng Ma, Mark Coates |
| 2021 | CIKM | Structure Aware Experience Replay for Incremental Learning in Graph-based Recommender Systems. | Kian Ahrabian, Yishi Xu, Yingxue Zhang, Jiapeng Wu, Yuening Wang, Mark Coates |
| 2021 | CIKM | Graph Representation Learning via Adversarial Variational Bayes. | Yunhe Li, Yaochen Hu, Yingxue Zhang |
| 2021 | CIKM | Graph Structure Aware Contrastive Knowledge Distillation for Incremental Learning in Recommender Systems. | Yuening Wang, Yingxue Zhang, Mark Coates |
| 2021 | ICCAD | Generalizable Cross-Graph Embedding for GNN-based Congestion Prediction. | Amur Ghose, Vincent Zhang, Yingxue Zhang, Dong Li, Wulong Liu, Mark Coates |
| 2021 | ICDM | C | Yingxue Zhang, Yanhua Li, Xun Zhou, Zhenming Liu, Jun Luo |
| 2021 | ICML | RNN with Particle Flow for Probabilistic Spatio-temporal Forecasting. | Soumyasundar Pal, Liheng Ma, Yingxue Zhang, Mark Coates |
| 2021 | KDD | Dual Graph enhanced Embedding Neural Network for CTR Prediction. | Wei Guo, Rong Su, Renhao Tan, Huifeng Guo, Yingxue Zhang, Zhirong Liu, Ruiming Tang, Xiuqiang He |
| 2021 | NAACL | Context Tracking Network: Graph-based Context Modeling for Implicit Discourse Relation Recognition. | Yingxue Zhang, Fandong Meng, Peng Li, Ping Jian, Jie Zhou |
| 2021 | NPC | Efficiency-First Fault-Tolerant Replica Scheduling Strategy for Reliability Constrained Cloud Application. | Yingxue Zhang, Guisheng Fan, Huiqun Yu, Xingpeng Chen |
| 2021 | PCS | No-reference Quality Assessment of Panoramic Video based on Spherical-domain Features. | Yingxue Zhang, Zizheng Liu, Zhenzhong Chen, Xiaozhong Xu, Shan Liu |
| 2021 | SIGIR | TIE: A Framework for Embedding-based Incremental Temporal Knowledge Graph Completion. | Jiapeng Wu, Yishi Xu, Yingxue Zhang, Chen Ma, Mark Coates, Jackie Chi Kit Cheung |
| 2020 | AAAI | Memory Augmented Graph Neural Networks for Sequential Recommendation. | Chen Ma, Liheng Ma, Yingxue Zhang, Jianing Sun, Xue Liu, Mark Coates |
| 2020 | CIKM | GraphSAIL: Graph Structure Aware Incremental Learning for Recommender Systems. | Yishi Xu, Yingxue Zhang, Wei Guo, Huifeng Guo, Ruiming Tang, Mark Coates |
| 2020 | ICDM | cST-ML: Continuous Spatial-Temporal Meta-Learning for Traffic Dynamics Prediction. | Yingxue Zhang, Yanhua Li, Xun Zhou, Jun Luo |
| 2020 | ICML | Active Learning on Attributed Graphs via Graph Cognizant Logistic Regression and Preemptive Query Generation. | Florence Regol, Soumyasundar Pal, Yingxue Zhang, Mark Coates |
| 2020 | KDD | Probabilistic Metric Learning with Adaptive Margin for Top-K Recommendation. | Chen Ma, Liheng Ma, Yingxue Zhang, Ruiming Tang, Xue Liu, Mark Coates |
| 2020 | KDD | A Framework for Recommending Accurate and Diverse Items Using Bayesian Graph Convolutional Neural Networks. | Jianing Sun, Wei Guo, Dengcheng Zhang, Yingxue Zhang, Florence Regol, Yaochen Hu, Huifeng Guo, Ruiming Tang, Han Yuan, Xiuqiang He, Mark Coates |
| 2020 | KDD | Curb-GAN: Conditional Urban Traffic Estimation through Spatio-Temporal Generative Adversarial Networks. | Yingxue Zhang, Yanhua Li, Xun Zhou, Xiangnan Kong, Jun Luo |
| 2020 | SIGIR | Neighbor Interaction Aware Graph Convolution Networks for Recommendation. | Jianing Sun, Yingxue Zhang, Wei Guo, Huifeng Guo, Ruiming Tang, Xiuqiang He, Chen Ma, Mark Coates |
| 2020 | UAI | Non Parametric Graph Learning for Bayesian Graph Neural Networks. | Soumyasundar Pal, Saber Malekmohammadi, Florence Regol, Yingxue Zhang, Yishi Xu, Mark Coates |
| 2019 | AAAI | Bayesian Graph Convolutional Neural Networks for Semi-Supervised Classification. | Yingxue Zhang, Soumyasundar Pal, Mark Coates, Deniz stebay |
| 2019 | ICDM | Multi-graph Convolution Collaborative Filtering. | Jianing Sun, Yingxue Zhang, Chen Ma, Mark Coates, Huifeng Guo, Ruiming Tang, Xiuqiang He |
| 2019 | ICDM | TrafficGAN: Off-Deployment Traffic Estimation with Traffic Generative Adversarial Networks. | Yingxue Zhang, Yanhua Li, Xun Zhou, Xiangnan Kong, Jun Luo |
| 2019 | VCIP | SSIM Prediction for H.265/HEVC based on Convolutional Neural Networks. | Sihan Wang, Yingxue Zhang, Daiqin Yang, Zhenzhong Chen |
| 2018 | CIKM | Point-of-Interest Recommendation: Exploiting Self-Attentive Autoencoders with Neighbor-Aware Influence. | Chen Ma, Yingxue Zhang, Qinglong Wang, Xue Liu |
| 2018 | ICASSP | A Graph-CNN for 3D Point Cloud Classification. | Yingxue Zhang, Michael G. Rabbat |
| 2016 | VCIP | Revisiting visual attention identification based on eye tracking data analytics. | Yingxue Zhang, Zhenzhong Chen |