PAGE: a partition aware graph computation engine. - Yingxia Shao; Junjie Yao; Bin Cui 001; Lin Ma 006 (CIKM, 2013)

bCATE: A Balanced Contention-Aware Transaction Execution Model for Highly Concurrent OLTP Systems. - Xiaogang Shi; Yanfei Lv; Yingxia Shao; Bin Cui 001 (WAIM, 2013)

Efficient cohesive subgraphs detection in parallel. - Yingxia Shao; Lei Chen 002; Bin Cui 001 (SIGMOD Conference, 2014)

Parallel subgraph listing in a large-scale graph. - Yingxia Shao; Bin Cui 001; Lei Chen 002; Lin Ma 006; Junjie Yao; Ning Xu (SIGMOD Conference, 2014)

Joint Modeling of User Check-in Behaviors for Point-of-Interest Recommendation. - Hongzhi Yin; Xiaofang Zhou 001; Yingxia Shao; Hao Wang 005; Shazia Sadiq (CIKM, 2015)

Exploiting Matrix Dependency for Efficient Distributed Matrix Computation. - Lele Yu; Yingxia Shao; Bin Cui 001 (SIGMOD Conference, 2015)

An Efficient Similarity Search Framework for SimRank over Large Dynamic Graphs. - Yingxia Shao; Bin Cui 001; Lei Chen 002; Mingming Liu; Xing Xie 001 (Proc. VLDB Endow., 2015)

PAGE: A Partition Aware Engine for Parallel Graph Computation. - Yingxia Shao; Bin Cui 001; Lin Ma 006 (IEEE Trans. Knowl. Data Eng., 2015)

Heterogeneous Environment Aware Streaming Graph Partitioning. - Ning Xu; Bin Cui 001; Lei Chen 002; Zi Huang; Yingxia Shao (IEEE Trans. Knowl. Data Eng., 2015)

Tornado: A System For Real-Time Iterative Analysis Over Evolving Data. - Xiaogang Shi; Bin Cui 001; Yingxia Shao; Yunhai Tong (SIGMOD Conference, 2016)

LDA*: A Robust and Large-scale Topic Modeling System. - Lele Yu; Bin Cui 001; Ce Zhang 001; Yingxia Shao (Proc. VLDB Endow., 2017)

An Experimental Evaluation of SimRank-based Similarity Search Algorithms. - Zhipeng Zhang; Yingxia Shao; Bin Cui 001; Ce Zhang 001 (Proc. VLDB Endow., 2017)

Fast Parallel Path Concatenation for Graph Extraction. - Yingxia Shao; Kai Lei; Lei Chen 002; Zi Huang; Bin Cui 001; Zhongyi Liu; Yunhai Tong; Jin Xu 002 (IEEE Trans. Knowl. Data Eng., 2017)

CUTE: Querying Knowledge Graphs by Tabular Examples. - Zichen Wang; Tian Li 005; Yingxia Shao; Bin Cui 001 (APWeb/WAIM (1), 2018)

GLM+: An Efficient System for Generalized Linear Models. - Lele Yu; Lingyu Wang; Yingxia Shao; Long Guo; Bin Cui 001 (BigComp, 2018)

Towards Reliable Learning for High Stakes Applications. - Jinyang Gao; Junjie Yao; Yingxia Shao (AAAI, 2019)

FeatureBand: A Feature Selection Method by Combining Early Stopping and Genetic Local Search. - Huanran Xue; Jiawei Jiang 001; Yingxia Shao; Bin Cui 001 (APWeb/WAIM (2), 2019)

Forecasting Pavement Performance with a Feature Fusion LSTM-BPNN Model. - Yushun Dong; Yingxia Shao; Xiaotong Li; Sili Li; Lei Quan; Wei Zhang 056; Junping Du 001 (CIKM, 2019)

Sparse Gradient Compression for Distributed SGD. - Haobo Sun; Yingxia Shao; Jiawei Jiang 001; Bin Cui 001; Kai Lei; Yu Xu; Jiang Wang (DASFAA (2), 2019)

NSCaching: Simple and Efficient Negative Sampling for Knowledge Graph Embedding. - Yongqi Zhang; Quanming Yao; Yingxia Shao; Lei Chen 002 (ICDE, 2019)

PS2: Parameter Server on Spark. - Zhipeng Zhang; Bin Cui 001; Yingxia Shao; Lele Yu; Jiawei Jiang 001; Xupeng Miao (SIGMOD Conference, 2019)

CNN Compression-Recovery Framework via Rank Allocation Decomposition With Knowledge Transfer. - Zhonghong Ou; Yunfeng Liu; Huihui Kong; Meina Song; Yingxia Shao (IEEE Access, 2019)

Fast De-anonymization of Social Networks with Structural Information. - Yingxia Shao; Jialin Liu; Shuyang Shi; Yuemei Zhang; Bin Cui 001 (Data Sci. Eng., 2019)

An Experimental Evaluation of Large Scale GBDT Systems. - Fangcheng Fu; Jiawei Jiang 001; Yingxia Shao; Bin Cui 001 (Proc. VLDB Endow., 2019)

Large-scale Graph Analysis: System, Algorithm and Optimization - Yingxia Shao; Bin Cui 001; Lei Chen 002 (Springer, 2020)

Efficient Automatic CASH via Rising Bandits. - Yang Li 106; Jiawei Jiang 001; Jinyang Gao; Yingxia Shao; Ce Zhang 001; Bin Cui 001 (AAAI, 2020)

Multiple Local Community Detection via High-Quality Seed Identification. - Jiaxu Liu; Yingxia Shao; Sen Su (APWeb/WAIM (1), 2020)

Densely-Connected Transformer with Co-attentive Information for Matching Text Sequences. - Minxu Zhang; Yingxia Shao; Kai Lei; Yuesheng Zhu; Bin Cui 001 (APWeb/WAIM (2), 2020)

Decentralized Embedding Framework for Large-Scale Networks. - Mubashir Imran; Hongzhi Yin; Tong Chen 005; Yingxia Shao; Xiangliang Zhang 001; Xiaofang Zhou 001 (DASFAA (3), 2020)

Efficient Diversity-Driven Ensemble for Deep Neural Networks. - Wentao Zhang 001; Jiawei Jiang 001; Yingxia Shao; Bin Cui 001 (ICDE, 2020)

Don't Waste Your Bits! Squeeze Activations and Gradients for Deep Neural Networks via TinyScript. - Fangcheng Fu; Yuzheng Hu; Yihan He; Jiawei Jiang 001; Yingxia Shao; Ce Zhang 001; Bin Cui 001 (ICML, 2020)

Memory-Aware Framework for Efficient Second-Order Random Walk on Large Graphs. - Yingxia Shao; Shiyue Huang; Xupeng Miao; Bin Cui 001; Lei Chen 002 (SIGMOD Conference, 2020)

Reliable Data Distillation on Graph Convolutional Network. - Wentao Zhang 001; Xupeng Miao; Yingxia Shao; Jiawei Jiang 001; Lei Chen 002; Olivier Ruas; Bin Cui 001 (SIGMOD Conference, 2020)

Snapshot boosting: a fast ensemble framework for deep neural networks. - Wentao Zhang 001; Jiawei Jiang 001; Yingxia Shao; Bin Cui 001 (Sci. China Inf. Sci., 2020)

DASFAA 20202 Special Issue Editorial. - Yingxia Shao; Yanyan Shen; Bin Cui 001; Jeffrey Xu Yu (Data Sci. Eng., 2020)

SKCompress: compressing sparse and nonuniform gradient in distributed machine learning. - Jiawei Jiang 001; Fangcheng Fu; Tong Yang 003; Yingxia Shao; Bin Cui 001 (VLDB J., 2020)

Multi-Modal COVID-19 Discovery With Collaborative Federated Learning. - Xiaomeng Chen; Yingxia Shao; Zhe Xue; Ziqiang Yu (CCIS, 2021)

Federated Graph Neural Network for Cross-graph Node Classification. - Zeli Guan; Yawen Li 001; Zhe Xue; Yuxin Liu; Hongrui Gao; Yingxia Shao (CCIS, 2021)

Urban Fatigue Driving Prediction With Federated Learning. - Yongqiang Ma; Yingxia Shao; Zhe Xue; Ziqiang Yu (CCIS, 2021)

Self-Supervised Graph Co-Training for Session-based Recommendation. - Xin Xia 013; Hongzhi Yin; Junliang Yu; Yingxia Shao; Lizhen Cui (CIKM, 2021)

Matching-oriented Embedding Quantization For Ad-hoc Retrieval. - Shitao Xiao; Zheng Liu 011; Yingxia Shao; Defu Lian; Xing Xie 001 (EMNLP (1), 2021)

CuWide: Towards Efficient Flow-based Training for Sparse Wide Models on GPUs (Extended Abstract). - Xupeng Miao; Lingxiao Ma; Zhi Yang 001; Yingxia Shao; Bin Cui 001; Lele Yu; Jiawei Jiang 001 (ICDE, 2021)

UniNet: Scalable Network Representation Learning with Metropolis-Hastings Sampling. - Xingyu Yao; Yingxia Shao; Bin Cui 001; Lei Chen 002 (ICDE, 2021)

DeGNN: Improving Graph Neural Networks with Graph Decomposition. - Xupeng Miao; Nezihe Merve Gürel; Wentao Zhang 001; Zhichao Han 001; Bo Li 026; Wei Min; Susie Xi Rao; Hansheng Ren; Yinan Shan; Yingxia Shao; Yujie Wang; Fan Wu 011; et al. (KDD, 2021)

VF2Boost: Very Fast Vertical Federated Gradient Boosting for Cross-Enterprise Learning. - Fangcheng Fu; Yingxia Shao; Lele Yu; Jiawei Jiang 001; Huanran Xue; Yangyu Tao; Bin Cui 001 (SIGMOD Conference, 2021)

Heterogeneity-Aware Distributed Machine Learning Training via Partial Reduce. - Xupeng Miao; Xiaonan Nie; Yingxia Shao; Zhi Yang 001; Jiawei Jiang 001; Lingxiao Ma; Bin Cui 001 (SIGMOD Conference, 2021)

Radio resource management algorithm for urban rail transit communication system based on Stackelberg game. - Yingxia Shao; Hailin Jiang; Hongli Zhao (VTC Spring, 2021)

Heterogeneous Hypergraph Embedding for Graph Classification. - Xiangguo Sun; Hongzhi Yin; Bo Liu 004; Hongxu Chen 002; Jiuxin Cao; Yingxia Shao; Nguyen Quoc Viet Hung (WSDM, 2021)

Training Microsoft News Recommenders with Pretrained Language Models in the Loop. - Shitao Xiao; Zheng Liu 011; Yingxia Shao; Tao Di; Xing Xie 001 (CoRR, 2021)

Search-oriented Differentiable Product Quantization. - Shitao Xiao; Zheng Liu 011; Yingxia Shao; Defu Lian; Xing Xie 001 (CoRR, 2021)

Multiple Local Community Detection via High-Quality Seed Identification over Both Static and Dynamic Networks. - Jiaxu Liu; Yingxia Shao; Sen Su (Data Sci. Eng., 2021)

Gated Graph Neural Attention Networks for abstractive summarization. - Zeyu Liang; Junping Du 001; Yingxia Shao; Houye Ji (Neurocomputing, 2021)

Sys-TM: A Fast and General Topic Modeling System. - Yingxia Shao; Xupeng Li; Yiru Chen; Lele Yu; Bin Cui 001 (IEEE Trans. Knowl. Data Eng., 2021)

Memory-aware framework for fast and scalable second-order random walk over billion-edge natural graphs. - Yingxia Shao; Shiyue Huang; Yawen Li 001; Xupeng Miao; Bin Cui 001; Lei Chen 002 (VLDB J., 2021)

A Relational Triple Extraction Method Based on Feature Reasoning for Technological Patents. - Runze Fang; Junping Du 001; Yingxia Shao; Zeli Guan (CCIS, 2022)

Adaptive Dual Channel Convolution Hypergraph Representation Learning for Technological Intellectual Property. - Yuxin Liu; Yawen Li 001; Yingxia Shao; Zeli Guan (CCIS, 2022)

Scalable Graph Sampling on GPUs with Compressed Graph. - Hongbo Yin; Yingxia Shao; Xupeng Miao; Yawen Li 001; Bin Cui 001 (CIKM, 2022)

RetroMAE: Pre-Training Retrieval-oriented Language Models Via Masked Auto-Encoder. - Shitao Xiao; Zheng Liu 011; Yingxia Shao; Zhao Cao (EMNLP, 2022)

Lasagne: A Multi-Layer Graph Convolutional Network Framework via Node-aware Deep Architecture (Extended Abstract). - Xupeng Miao; Wentao Zhang 001; Yingxia Shao; Bin Cui 001; Lei Chen 002; Ce Zhang 001; Jiawei Jiang 001 (ICDE, 2022)

Training Large-Scale News Recommenders with Pretrained Language Models in the Loop. - Shitao Xiao; Zheng Liu 011; Yingxia Shao; Tao Di; Bhuvan Middha; Fangzhao Wu; Xing Xie 001 (KDD, 2022)

Uni-Retriever: Towards Learning the Unified Embedding Based Retriever in Bing Sponsored Search. - Jianjin Zhang; Zheng Liu 011; Weihao Han; Shitao Xiao; Ruicheng Zheng; Yingxia Shao; Hao Sun 015; Hanqing Zhu; Premkumar Srinivasan; Weiwei Deng; Qi Zhang 066; Xing Xie 001 (KDD, 2022)

Distill-VQ: Learning Retrieval Oriented Vector Quantization By Distilling Knowledge from Dense Embeddings. - Shitao Xiao; Zheng Liu 011; Weihao Han; Jianjin Zhang; Defu Lian; Yeyun Gong; Qi Chen 009; Fan Yang 024; Hao Sun 015; Yingxia Shao; Xing Xie 001 (SIGIR, 2022)

Space4HGNN: A Novel, Modularized and Reproducible Platform to Evaluate Heterogeneous Graph Neural Network. - Tianyu Zhao; Cheng Yang 002; Yibo Li; Quan Gan; Zhenyi Wang; Fengqi Liang; Huan Zhao 002; Yingxia Shao; Xiao Wang 017; Chuan Shi 001 (SIGIR, 2022)

Progressively Optimized Bi-Granular Document Representation for Scalable Embedding Based Retrieval. - Shitao Xiao; Zheng Liu 011; Weihao Han; Jianjin Zhang; Yingxia Shao; Defu Lian; Chaozhuo Li; Hao Sun 015; Denvy Deng; Liangjie Zhang; Qi Zhang 066; Xing Xie 001 (WWW, 2022)

LECF: recommendation via learnable edge collaborative filtering. - Shitao Xiao; Yingxia Shao; Yawen Li 001; Hongzhi Yin; Yanyan Shen; Bin Cui 001 (Sci. China Inf. Sci., 2022)

Uni-Retriever: Towards Learning The Unified Embedding Based Retriever in Bing Sponsored Search. - Jianjin Zhang; Zheng Liu 011; Weihao Han; Shitao Xiao; Ruicheng Zheng; Yingxia Shao; Hao Sun 015; Hanqing Zhu; Premkumar Srinivasan; Denvy Deng; Qi Zhang 066; Xing Xie 001 (CoRR, 2022)

An Intellectual Property Entity Recognition Method Based on Transformer and Technological Word Information. - Yuhui Wang; Junping Du 001; Yingxia Shao (CoRR, 2022)

Scientific and Technological Text Knowledge Extraction Method of based on Word Mixing and GRU. - Suyu Ouyang; Yingxia Shao; Junping Du 001; Ang Li 015 (CoRR, 2022)

Distill-VQ: Learning Retrieval Oriented Vector Quantization By Distilling Knowledge from Dense Embeddings. - Shitao Xiao; Zheng Liu 011; Weihao Han; Jianjin Zhang; Defu Lian; Yeyun Gong; Qi Chen 009; Fan Yang 024; Hao Sun 015; Yingxia Shao; Denvy Deng; Qi Zhang 001; et al. (CoRR, 2022)

Retrieval of Scientific and Technological Resources for Experts and Scholars. - Suyu Ouyang; Yingxia Shao; Ang Li 015 (CoRR, 2022)

Research on Intellectual Property Resource Profile and Evolution Law. - Yuhui Wang; Yingxia Shao; Ang Li 015 (CoRR, 2022)

RetroMAE: Pre-training Retrieval-oriented Transformers via Masked Auto-Encoder. - Zheng Liu 011; Yingxia Shao (CoRR, 2022)

Sentiment Analysis of Online Travel Reviews Based on Capsule Network and Sentiment Lexicon. - Jia Wang; Junping Du 001; Yingxia Shao; Ang Li 015 (CoRR, 2022)

A sentiment analysis model for car review texts based on adversarial training and whole word mask BERT. - Xingchen Liu; Yawen Li 001; Yingxia Shao; Ang Li 015; Jian Liang (CoRR, 2022)

Social Network Community Detection Based on Textual Content Similarity and Sentimental Tendency. - Jie Gao; Junping Du 001; Yingxia Shao; Ang Li 015; Zeli Guan (CoRR, 2022)

A Rare Topic Discovery Model for Short Texts Based on Co-occurrence word Network. - Chengjie Ma; Junping Du 001; Yingxia Shao; Ang Li 015; Zeli Guan (CoRR, 2022)

Diffusion Models: A Comprehensive Survey of Methods and Applications. - Ling Yang 006; Zhilong Zhang; Yang Song 011; Shenda Hong; Runsheng Xu; Yue Zhao 016; Yingxia Shao; Wentao Zhang 001; Ming-Hsuan Yang 001; Bin Cui 001 (CoRR, 2022)

Efficient Graph Neural Network Inference at Large Scale. - Xinyi Gao 001; Wentao Zhang 001; Yingxia Shao; Quoc Viet Hung Nguyen; Bin Cui 001; Hongzhi Yin (CoRR, 2022)

An I/O-Efficient Disk-based Graph System for Scalable Second-Order Random Walk of Large Graphs. - Hongzheng Li; Yingxia Shao; Junping Du 001; Bin Cui 001; Lei Chen 002 (Proc. VLDB Endow., 2022)

SANCUS: Staleness-Aware Communication-Avoiding Full-Graph Decentralized Training in Large-Scale Graph Neural Networks. - Jingshu Peng; Zhao Chen 003; Yingxia Shao; Yanyan Shen; Lei Chen 002; Jiannong Cao 001 (Proc. VLDB Endow., 2022)

CuWide: Towards Efficient Flow-Based Training for Sparse Wide Models on GPUs. - Xupeng Miao; Lingxiao Ma; Zhi Yang 001; Yingxia Shao; Bin Cui 001; Lele Yu; Jiawei Jiang 001 (IEEE Trans. Knowl. Data Eng., 2022)

Causal Intervention and Counterfactual Reasoning for Multi-modal Fake News Detection. - Ziwei Chen; Linmei Hu; Weixin Li 001; Yingxia Shao; Liqiang Nie (ACL (1), 2023)

RetroMAE-2: Duplex Masked Auto-Encoder For Pre-Training Retrieval-Oriented Language Models. - Zheng Liu 011; Shitao Xiao; Yingxia Shao; Zhao Cao (ACL (1), 2023)

Knowledgeable Parameter Efficient Tuning Network for Commonsense Question Answering. - Ziwang Zhao; Linmei Hu; Hanyu Zhao; Yingxia Shao; Yequan Wang (ACL (1), 2023)

Diversity-aware Deep Ranking Network for Recommendation. - Zihong Wang; Yingxia Shao; Jiyuan He; Jinbao Liu; Shitao Xiao; Tao Feng; Ming Liu (CIKM, 2023)

Sancus: Staleness-Aware Communication-Avoiding Full-Graph Decentralized Training in Large-Scale Graph Neural Networks (Extended Abstract). - Jingshu Peng; Zhao Chen 003; Yingxia Shao; Yanyan Shen; Lei Chen 002; Jiannong Cao 001 (IJCAI, 2023)

LibVQ: A Toolkit for Optimizing Vector Quantization and Efficient Neural Retrieval. - Chaofan Li; Zheng Liu 011; Shitao Xiao; Yingxia Shao; Defu Lian; Zhao Cao (SIGIR, 2023)

Entity Alignment Method of Science and Technology Patent based on Graph Convolution Network and Information Fusion. - Runze Fang; Yawen Li 001; Yingxia Shao; Zeli Guan; Zhe Xue (CoRR, 2023)

Dynamic Fair Federated Learning Based on Reinforcement Learning. - Weikang Chen; Junping Du 001; Yingxia Shao; Jia Wang; Yangxi Zhou (CoRR, 2023)

Relation Extraction Model Based on Semantic Enhancement Mechanism. - Peiyu Liu; Junping Du 001; Yingxia Shao; Zeli Guan (CoRR, 2023)

Making Large Language Models A Better Foundation For Dense Retrieval. - Chaofan Li; Zheng Liu 011; Shitao Xiao; Yingxia Shao (CoRR, 2023)

DUCATI: A Dual-Cache Training System for Graph Neural Networks on Giant Graphs with the GPU. - Xin Zhang 101; Yanyan Shen; Yingxia Shao; Lei Chen 002 (Proc. ACM Manag. Data, 2023)

ContTune: Continuous Tuning by Conservative Bayesian Optimization for Distributed Stream Data Processing Systems. - Jinqing Lian; Xinyi Zhang 002; Yingxia Shao; Zenglin Pu; Qingfeng Xiang; Yawen Li 001; Bin Cui 001 (Proc. VLDB Endow., 2023)

Lasagne: A Multi-Layer Graph Convolutional Network Framework via Node-Aware Deep Architecture. - Xupeng Miao; Wentao Zhang 001; Yingxia Shao; Bin Cui 001; Lei Chen 002; Ce Zhang 001; Jiawei Jiang 001 (IEEE Trans. Knowl. Data Eng., 2023)

P2CG: a privacy preserving collaborative graph neural network training framework. - Xupeng Miao; Wentao Zhang 001; Yuezihan Jiang; Fangcheng Fu; Yingxia Shao; Lei Chen 002; Yangyu Tao; Gang Cao; Bin Cui 001 (VLDB J., 2023)

Multi-View Scholar Clustering With Dynamic Interest Tracking. - Ang Li 015; Yawen Li 001; Yingxia Shao; Bingyan Liu (IEEE Trans. Knowl. Data Eng., 2023)

Experimental Analysis of Large-scale Learnable Vector Storage Compression. - Hailin Zhang 004; Penghao Zhao; Xupeng Miao; Yingxia Shao; Zirui Liu 002; Tong Yang 003; Bin Cui 001 (Proc. VLDB Endow., 2023)

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 (AAAI, 2024)

Llama2Vec: Unsupervised Adaptation of Large Language Models for Dense Retrieval. - Chaofan Li; Zheng Liu 011; Shitao Xiao; Yingxia Shao; Defu Lian (ACL (1), 2024)

Distribution-Aware Diversification for Personalized Re-ranking in Recommendation. - Zihong Wang; Yingxia Shao; Jiyuan He; Jinbao Liu (APWeb/WAIM (2), 2024)

Accelerating Scalable Graph Neural Network Inference with Node-Adaptive Propagation. - Xinyi Gao 001; Wentao Zhang 001; Junliang Yu; Yingxia Shao; Quoc Viet Hung Nguyen; Bin Cui 001; Hongzhi Yin (ICDE, 2024)

NovaChart: A Large-scale Dataset towards Chart Understanding and Generation of Multimodal Large Language Models. - Linmei Hu; Duokang Wang; Yiming Pan 003; Jifan Yu; Yingxia Shao; Chong Feng 001; Liqiang Nie (ACM Multimedia, 2024)

SpanGNN: Towards Memory-Efficient Graph Neural Networks via Spanning Subgraph Training. - Xizhi Gu; Hongzheng Li; Shihong Gao; Xinyan Zhang; Lei Chen 002; Yingxia Shao (ECML/PKDD (3), 2024)

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 (SIGIR, 2024)

LLMvsSmall Model? Large Language Model Based Text Augmentation Enhanced Personality Detection Model. - Linmei Hu; Hongyu He; Duokang Wang; Ziwang Zhao; Yingxia Shao; Liqiang Nie (CoRR, 2024)

Token-Efficient Leverage Learning in Large Language Models. - Yuanhao Zeng; Min Wang; Yihang Wang; Yingxia Shao (CoRR, 2024)

ChatBI: Towards Natural Language to Complex Business Intelligence SQL. - Jinqing Lian; Xinyi Liu; Yingxia Shao; Yang Dong; Ming Wang; Zhang Wei; Tianqi Wan; Ming Dong; Hailin Yan (CoRR, 2024)

SEA-SQL: Semantic-Enhanced Text-to-SQL with Adaptive Refinement. - Chaofan Li; Yingxia Shao; Zheng Liu 011 (CoRR, 2024)

Adversarial Contrastive Learning Based Physics-Informed Temporal Networks for Cuffless Blood Pressure Estimation. - Rui Wang; Mengshi Qi; Yingxia Shao; Anfu Zhou; Huadong Ma (CoRR, 2024)

DELIA: Diversity-Enhanced Learning for Instruction Adaptation in Large Language Models. - Yuanhao Zeng; Fei Ren; Xinpeng Zhou; Yihang Wang; Yingxia Shao (CoRR, 2024)

LAC: Graph Contrastive Learning with Learnable Augmentation in Continuous Space. - Zhenyu Lin; Hongzheng Li; Yingxia Shao; Guanhua Ye; Yawen Li 001; Quanqing Xu (CoRR, 2024)

SIMPLE: Efficient Temporal Graph Neural Network Training at Scale with Dynamic Data Placement. - Shihong Gao; Yiming Li; Xin Zhang 101; Yanyan Shen; Yingxia Shao; Lei Chen 002 (Proc. ACM Manag. Data, 2024)

ETC: Efficient Training of Temporal Graph Neural Networks over Large-scale Dynamic Graphs. - Shihong Gao; Yiming Li; Yanyan Shen; Yingxia Shao; Lei Chen 002 (Proc. VLDB Endow., 2024)

DAHA: Accelerating GNN Training with Data and Hardware Aware Execution Planning. - Zhiyuan Li; Xun Jian 001; Yue Wang 012; Yingxia Shao; Lei Chen 002 (Proc. VLDB Endow., 2024)

How good are machine learning clouds? Benchmarking two snapshots over 5 years. - Jiawei Jiang 001; Yi Wei; Yu Liu 075; Wentao Wu 001; Chuang Hu; Zhigao Zheng 001; Ziyi Zhang; Yingxia Shao; Ce Zhang 001 (VLDB J., 2024)

Federated learning for supervised cross-modal retrieval. - Ang Li 015; Yawen Li 001; Yingxia Shao (World Wide Web (WWW), 2024)

Distributed Graph Neural Network Training: A Survey. - Yingxia Shao; Hongzheng Li; Xizhi Gu; Hongbo Yin; Yawen Li 001; Xupeng Miao; Wentao Zhang 001; Bin Cui 001; Lei Chen 002 (ACM Comput. Surv., 2024)

Reinforcement Active Client Selection for Federated Heterogeneous Graph Learning. - Jia Wang; Yawen Li 001; Yingxia Shao; Zhe Xue; Zeli Guan; Ang Li 015; Guanhua Ye (AAAI, 2025)

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 011 (ACL (1), 2025)

MSformer: Joint Prediction of Multi-Dimensional Resources in Computing Power Network based on Multi-Granularity Sampling. - Jiuzhao Yang; Junping Du 001; Yingxia Shao; Yawen Li 001; Ang Li 015; Guanhua Ye (BigComp, 2025)

Towards Scalable and Efficient Graph Structure Learning. - Siqi Shen; Wentao Zhang 001; Chengshuo Du; Chong Chen 001; Fangcheng Fu; Yingxia Shao; Bin Cui 001 (ICDE, 2025)

Making Text Embedders Few-Shot Learners. - Chaofan Li; Minghao Qin; Shitao Xiao; Jianlyu Chen; Kun Luo; Defu Lian; Yingxia Shao; Zheng Liu 011 (ICLR, 2025)

Fitting Into Any Shape: A Flexible LLM-Based Re-Ranker With Configurable Depth and Width. - Zheng Liu 011; Chaofan Li; Shitao Xiao; Chaozhuo Li; Chen Jason Zhang; Hao Liao; Defu Lian; Yingxia Shao (WWW, 2025)

Horizontal Federated Heterogeneous Graph Learning: A Multi-Scale Adaptive Solution to Data Distribution Challenges. - Jia Wang; Yawen Li 001; Zhe Xue; Yingxia Shao; Zeli Guan; Wenling Li (WWW, 2025)

Distributed Database Diagnosis Method for Compound Anomalies. - Qingfeng Xiang; Yingxia Shao; Quanqing Xu; Chuanhui Yang (Int. J. Softw. Informatics, 2025)

Matryoshka Re-Ranker: A Flexible Re-Ranking Architecture With Configurable Depth and Width. - Zheng Liu 011; Chaofan Li; Shitao Xiao; Chaozhuo Li; Defu Lian; Yingxia Shao (CoRR, 2025)

Reinforced Information Retrieval. - Chaofan Li; Zheng Liu 011; Jianlyv Chen; Defu Lian; Yingxia Shao (CoRR, 2025)

From Sancus to Sancusq: staleness and quantization-aware full-graph decentralized training in graph neural networks. - Jingshu Peng; Qiyu Liu; Zhao Chen 003; Yingxia Shao; Yanyan Shen; Lei Chen 002; Jiannong Cao 001 (VLDB J., 2025)

FG-RAG: Enhancing Query-Focused Summarization with Context-Aware Fine-Grained Graph RAG. - Yubin Hong; Chaofan Li; Jingyi Zhang; Yingxia Shao (CoRR, 2025)

Towards A Generalist Code Embedding Model Based On Massive Data Synthesis. - Chaofan Li; Jianlyu Chen; Yingxia Shao; Defu Lian; Zheng Liu 011 (CoRR, 2025)

Piecewise Linear Approximation in Learned Index Structures: Theoretical and Empirical Analysis. - Jiayong Qin; Xianyu Zhu; Qiyu Liu; Guangyi Zhang; Zhigang Cai; Jianwei Liao 001; Sha Hu; Jingshu Peng; Yingxia Shao; Lei Chen 002 (CoRR, 2025)