| 2026 | AAAI | HFR-MKGC: Hierarchical Fusion Reasoning with MLLMs for Multi-modal Knowledge Graph Completion. | Di Wang, Junping Du, Zhe Xue, Meiyu Liang, Guanhua Ye, Yingxia Shao, Haisheng Li |
| 2026 | AAAI | Rethink Representation Learning for Questionnaire Data. | Guanhua Ye, Jifeng He, Yan Li, Junping Du, Zhe Xue, Yingxia Shao, Meiyu Liang, Yawen Li |
| 2026 | DASFAA | DBRooter: An Efficient Causal Root Cause Analysis Framework for Distributed Databases. | Qingfeng Xiang, Yingxia Shao, Chenglin Tian, Quanqing Xu, Qiyao Luo |
| 2026 | ICDE | JITPrune: An Efficient Online Feature Pruning Framework for Embedding-Based DLRM Training. | Hongzheng Li, Yucheng Wu, Junjie Zhai, Anan Liu, Yuekui Yang, Yingxia Shao |
| 2026 | ICDE | LLMSQLMUTATOR: LLM-Powered Test Case Generation for Database Using Bug Reports. | Chenglin Tian, Chaofan Li, Yawen Li, Yingxia Shao |
| 2025 | AAAI | Reinforcement Active Client Selection for Federated Heterogeneous Graph Learning. | Jia Wang, Yawen Li, Yingxia Shao, Zhe Xue, Zeli Guan, Ang Li, Guanhua Ye |
| 2025 | ACL | Reinforced IR: A Self-Boosting Framework For Domain-Adapted Information Retrieval. | Chaofan Li, Jianlyu Chen, Yingxia Shao, Chaozhuo Li, Quanqing Xu, Defu Lian, Zheng Liu |
| 2025 | ADC | Federated Learning for Computing Power Network: A Latency Optimization Scheduling Framework Based on Deep Reinforcement Learning. | Zhonghui Ma, Junping Du, Zhe Xue, Guanhua Ye, Yingxia Shao |
| 2025 | ADC | LHATM: LLM-Guided Hierarchy-Aware Topic Modeling Framework. | Zheng Zhang, Junping Du, Yingxia Shao, Guanhua Ye |
| 2025 | CIKM | Context-Aware Fine-Grained Graph RAG for Query-Focused Summarization. | Yubin Hong, Chaofan Li, Jingyi Zhang, Yingxia Shao |
| 2025 | ICDE | Towards Scalable and Efficient Graph Structure Learning. | Siqi Shen, Wentao Zhang, Chengshuo Du, Chong Chen, Fangcheng Fu, Yingxia Shao, Bin Cui |
| 2025 | ICLR | Making Text Embedders Few-Shot Learners. | Chaofan Li, Minghao Qin, Shitao Xiao, Jianlyu Chen, Kun Luo, Defu Lian, Yingxia Shao, Zheng Liu |
| 2025 | IJCAI | CSAHFL: Clustered Semi-Asynchronous Hierarchical Federated Learning for Dual-layer Non-IID in Heterogeneous Edge Computing Networks. | Aijing Li, Junping Du, Dandan Liu, Yingxia Shao, Tong Zhao, Guanhua Ye |
| 2025 | ICS | CoLa: Towards Communication-efficient Distributed Sparse Matrix-Matrix Multiplication on GPUs. | Lixing Zhang, Yingxia Shao, Shigang Li |
| 2025 | KDD | LLMs Are Noisy Oracles! LLM-based Noise-aware Graph Active Learning for Node Classification. | Zeang Sheng, Weiyang Guo, Yingxia Shao, Wentao Zhang, Bin Cui |
| 2025 | WWW | Fitting Into Any Shape: A Flexible LLM-Based Re-Ranker With Configurable Depth and Width. | Zheng Liu, Chaofan Li, Shitao Xiao, Chaozhuo Li, Chen Jason Zhang, Hao Liao, Defu Lian, Yingxia Shao |
| 2025 | WWW | Horizontal Federated Heterogeneous Graph Learning: A Multi-Scale Adaptive Solution to Data Distribution Challenges. | Jia Wang, Yawen Li, Zhe Xue, Yingxia Shao, Zeli Guan, Wenling Li |
| 2024 | AAAI | LLM vs Small Model? Large Language Model Based Text Augmentation Enhanced Personality Detection Model. | Linmei Hu, Hongyu He, Duokang Wang, Ziwang Zhao, Yingxia Shao, Liqiang Nie |
| 2024 | ACL | Llama2Vec: Unsupervised Adaptation of Large Language Models for Dense Retrieval. | Chaofan Li, Zheng Liu, Shitao Xiao, Yingxia Shao, Defu Lian |
| 2024 | APWEB | Distribution-Aware Diversification for Personalized Re-ranking in Recommendation. | Zihong Wang, Yingxia Shao, Jiyuan He, Jinbao Liu |
| 2024 | ICDE | Accelerating Scalable Graph Neural Network Inference with Node-Adaptive Propagation. | Xinyi Gao, Wentao Zhang, Junliang Yu, Yingxia Shao, Quoc Viet Hung Nguyen, Bin Cui, Hongzhi Yin |
| 2024 | SIGIR | Let Me Show You Step by Step: An Interpretable Graph Routing Network for Knowledge-based Visual Question Answering. | Duokang Wang, Linmei Hu, Rui Hao, Yingxia Shao, Xin Lv, Liqiang Nie, Juanzi Li |
| 2023 | ACL | Causal Intervention and Counterfactual Reasoning for Multi-modal Fake News Detection. | Ziwei Chen, Linmei Hu, Weixin Li, Yingxia Shao, Liqiang Nie |
| 2023 | ACL | RetroMAE-2: Duplex Masked Auto-Encoder For Pre-Training Retrieval-Oriented Language Models. | Zheng Liu, Shitao Xiao, Yingxia Shao, Zhao Cao |
| 2023 | ACL | Knowledgeable Parameter Efficient Tuning Network for Commonsense Question Answering. | Ziwang Zhao, Linmei Hu, Hanyu Zhao, Yingxia Shao, Yequan Wang |
| 2023 | CIKM | Diversity-aware Deep Ranking Network for Recommendation. | Zihong Wang, Yingxia Shao, Jiyuan He, Jinbao Liu, Shitao Xiao, Tao Feng, Ming Liu |
| 2023 | IJCAI | Sancus: Staleness-Aware Communication-Avoiding Full-Graph Decentralized Training in Large-Scale Graph Neural Networks (Extended Abstract). | Jingshu Peng, Zhao Chen, Yingxia Shao, Yanyan Shen, Lei Chen, Jiannong Cao |
| 2023 | SIGIR | LibVQ: A Toolkit for Optimizing Vector Quantization and Efficient Neural Retrieval. | Chaofan Li, Zheng Liu, Shitao Xiao, Yingxia Shao, Defu Lian, Zhao Cao |
| 2022 | CIKM | Scalable Graph Sampling on GPUs with Compressed Graph. | Hongbo Yin, Yingxia Shao, Xupeng Miao, Yawen Li, Bin Cui |
| 2022 | EMNLP | RetroMAE: Pre-Training Retrieval-oriented Language Models Via Masked Auto-Encoder. | Shitao Xiao, Zheng Liu, Yingxia Shao, Zhao Cao |
| 2022 | ICDE | Lasagne: A Multi-Layer Graph Convolutional Network Framework via Node-aware Deep Architecture (Extended Abstract). | Xupeng Miao, Wentao Zhang, Yingxia Shao, Bin Cui, Lei Chen, Ce Zhang, Jiawei Jiang |
| 2022 | KDD | Training Large-Scale News Recommenders with Pretrained Language Models in the Loop. | Shitao Xiao, Zheng Liu, Yingxia Shao, Tao Di, Bhuvan Middha, Fangzhao Wu, Xing Xie |
| 2022 | KDD | Uni-Retriever: Towards Learning the Unified Embedding Based Retriever in Bing Sponsored Search. | Jianjin Zhang, Zheng Liu, Weihao Han, Shitao Xiao, Ruicheng Zheng, Yingxia Shao, Hao Sun, Hanqing Zhu, Premkumar Srinivasan, Weiwei Deng, Qi Zhang, Xing Xie |
| 2022 | WWW | Progressively Optimized Bi-Granular Document Representation for Scalable Embedding Based Retrieval. | Shitao Xiao, Zheng Liu, Weihao Han, Jianjin Zhang, Yingxia Shao, Defu Lian, Chaozhuo Li, Hao Sun, Denvy Deng, Liangjie Zhang, Qi Zhang, Xing Xie |
| 2022 | SIGIR | Distill-VQ: Learning Retrieval Oriented Vector Quantization By Distilling Knowledge from Dense Embeddings. | Shitao Xiao, Zheng Liu, Weihao Han, Jianjin Zhang, Defu Lian, Yeyun Gong, Qi Chen, Fan Yang, Hao Sun, Yingxia Shao, Xing Xie |
| 2022 | SIGIR | Space4HGNN: A Novel, Modularized and Reproducible Platform to Evaluate Heterogeneous Graph Neural Network. | Tianyu Zhao, Cheng Yang, Yibo Li, Quan Gan, Zhenyi Wang, Fengqi Liang, Huan Zhao, Yingxia Shao, Xiao Wang, Chuan Shi |
| 2021 | CIKM | Self-Supervised Graph Co-Training for Session-based Recommendation. | Xin Xia, Hongzhi Yin, Junliang Yu, Yingxia Shao, Lizhen Cui |
| 2021 | EMNLP | Matching-oriented Embedding Quantization For Ad-hoc Retrieval. | Shitao Xiao, Zheng Liu, Yingxia Shao, Defu Lian, Xing Xie |
| 2021 | ICDE | CuWide: Towards Efficient Flow-based Training for Sparse Wide Models on GPUs (Extended Abstract). | Xupeng Miao, Lingxiao Ma, Zhi Yang, Yingxia Shao, Bin Cui, Lele Yu, Jiawei Jiang |
| 2021 | ICDE | UniNet: Scalable Network Representation Learning with Metropolis-Hastings Sampling. | Xingyu Yao, Yingxia Shao, Bin Cui, Lei Chen |
| 2021 | KDD | DeGNN: Improving Graph Neural Networks with Graph Decomposition. | Xupeng Miao, Nezihe Merve Grel, Wentao Zhang, Zhichao Han, Bo Li, Wei Min, Susie Xi Rao, Hansheng Ren, Yinan Shan, Yingxia Shao, Yujie Wang, Fan Wu, Hui Xue, Yaming Yang, Zitao Zhang, Yang Zhao, Shuai Zhang, Yujing Wang, Bin Cui, Ce Zhang |
| 2021 | VTC | Radio resource management algorithm for urban rail transit communication system based on Stackelberg game. | Yingxia Shao, Hailin Jiang, Hongli Zhao |
| 2021 | SIGMOD | VF | Fangcheng Fu, Yingxia Shao, Lele Yu, Jiawei Jiang, Huanran Xue, Yangyu Tao, Bin Cui |
| 2021 | SIGMOD | Heterogeneity-Aware Distributed Machine Learning Training via Partial Reduce. | Xupeng Miao, Xiaonan Nie, Yingxia Shao, Zhi Yang, Jiawei Jiang, Lingxiao Ma, Bin Cui |
| 2021 | WSDM | Heterogeneous Hypergraph Embedding for Graph Classification. | Xiangguo Sun, Hongzhi Yin, Bo Liu, Hongxu Chen, Jiuxin Cao, Yingxia Shao, Nguyen Quoc Viet Hung |
| 2020 | AAAI | Efficient Automatic CASH via Rising Bandits. | Yang Li, Jiawei Jiang, Jinyang Gao, Yingxia Shao, Ce Zhang, Bin Cui |
| 2020 | APWEB | Multiple Local Community Detection via High-Quality Seed Identification. | Jiaxu Liu, Yingxia Shao, Sen Su |
| 2020 | APWEB | Densely-Connected Transformer with Co-attentive Information for Matching Text Sequences. | Minxu Zhang, Yingxia Shao, Kai Lei, Yuesheng Zhu, Bin Cui |
| 2020 | DASFAA | Decentralized Embedding Framework for Large-Scale Networks. | Mubashir Imran, Hongzhi Yin, Tong Chen, Yingxia Shao, Xiangliang Zhang, Xiaofang Zhou |
| 2020 | ICDE | Efficient Diversity-Driven Ensemble for Deep Neural Networks. | Wentao Zhang, Jiawei Jiang, Yingxia Shao, Bin Cui |
| 2020 | ICML | Don't Waste Your Bits! Squeeze Activations and Gradients for Deep Neural Networks via TinyScript. | Fangcheng Fu, Yuzheng Hu, Yihan He, Jiawei Jiang, Yingxia Shao, Ce Zhang, Bin Cui |
| 2020 | SIGMOD | Memory-Aware Framework for Efficient Second-Order Random Walk on Large Graphs. | Yingxia Shao, Shiyue Huang, Xupeng Miao, Bin Cui, Lei Chen |
| 2020 | SIGMOD | Reliable Data Distillation on Graph Convolutional Network. | Wentao Zhang, Xupeng Miao, Yingxia Shao, Jiawei Jiang, Lei Chen, Olivier Ruas, Bin Cui |
| 2019 | AAAI | Towards Reliable Learning for High Stakes Applications. | Jinyang Gao, Junjie Yao, Yingxia Shao |
| 2019 | APWEB | FeatureBand: A Feature Selection Method by Combining Early Stopping and Genetic Local Search. | Huanran Xue, Jiawei Jiang, Yingxia Shao, Bin Cui |
| 2019 | CIKM | Forecasting Pavement Performance with a Feature Fusion LSTM-BPNN Model. | Yushun Dong, Yingxia Shao, Xiaotong Li, Sili Li, Lei Quan, Wei Zhang, Junping Du |
| 2019 | DASFAA | Sparse Gradient Compression for Distributed SGD. | Haobo Sun, Yingxia Shao, Jiawei Jiang, Bin Cui, Kai Lei, Yu Xu, Jiang Wang |
| 2019 | ICDE | NSCaching: Simple and Efficient Negative Sampling for Knowledge Graph Embedding. | Yongqi Zhang, Quanming Yao, Yingxia Shao, Lei Chen |
| 2019 | SIGMOD | PS2: Parameter Server on Spark. | Zhipeng Zhang, Bin Cui, Yingxia Shao, Lele Yu, Jiawei Jiang, Xupeng Miao |
| 2018 | APWEB | CUTE: Querying Knowledge Graphs by Tabular Examples. | Zichen Wang, Tian Li, Yingxia Shao, Bin Cui |
| 2018 | ICDE | Fast Parallel Path Concatenation for Graph Extraction. | Yingxia Shao, Kai Lei, Lei Chen, Zi Huang, Bin Cui, Zhongyi Liu, Yunhai Tong, Jin Xu |
| 2016 | SIGMOD | Tornado: A System For Real-Time Iterative Analysis Over Evolving Data. | Xiaogang Shi, Bin Cui, Yingxia Shao, Yunhai Tong |
| 2015 | CIKM | Joint Modeling of User Check-in Behaviors for Point-of-Interest Recommendation. | Hongzhi Yin, Xiaofang Zhou, Yingxia Shao, Hao Wang, Shazia Sadiq |
| 2015 | SIGMOD | Exploiting Matrix Dependency for Efficient Distributed Matrix Computation. | Lele Yu, Yingxia Shao, Bin Cui |
| 2014 | SIGMOD | Efficient cohesive subgraphs detection in parallel. | Yingxia Shao, Lei Chen, Bin Cui |
| 2014 | SIGMOD | Parallel subgraph listing in a large-scale graph. | Yingxia Shao, Bin Cui, Lei Chen, Lin Ma, Junjie Yao, Ning Xu |
| 2013 | CIKM | PAGE: a partition aware graph computation engine. | Yingxia Shao, Junjie Yao, Bin Cui, Lin Ma |