Yongchao Liu

According to our database, Yongchao Liu authored at least 73 papers between 2009 and 2025.

Collaborative distances:

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

2025

Learning Unified User Quantized Tokenizers for User Representation.

Chuan He, Yang Chen, Wuliang Huang, Tianyi Zheng, Jianhu Chen, Bin Dou, Yice Luo, Yun Zhu, Baokun Wang, Yongchao Liu, Xing Fu, Yu Cheng, Chuntao Hong, Weiqiang Wang, Xin-Wei Yao

CoRR, August, 2025

M^2VAE: Multi-Modal Multi-View Variational Autoencoder for Cold-start Item Recommendation.

Chuan He, Yongchao Liu, Qiang Li, Wenliang Zhong, Chuntao Hong, Xin Yao

CoRR, August, 2025

Community Detection in Heterogeneous Information Networks Without Materialization.

Jiaxin Jiang, Siyuan Yao, Yuhang Chen, Bingsheng He, Yudong Niu, Yuchen Li, Shixuan Sun, Yongchao Liu

Proc. ACM Manag. Data, June, 2025

<i>OTM</i>: Efficient <i>k</i>-Order-Based Core Maintenance in Large-Scale Dynamic Hypergraphs.

Xiangfei Fang, Chengying Huan, Heng Zhang, Yongchao Liu, Shaonan Ma, Yanjun Wu, Chen Zhao

ACM Trans. Knowl. Discov. Data, April, 2025

Building Robust and Trustworthy HGNN Models: A Learnable Threshold Approach for Node Classification.

Li Ma, Yongchao Liu, Xiaofeng Gao, Peng Zhang, Chuntao Hong

ACM Trans. Knowl. Discov. Data, February, 2025

GraphCLIP: Enhancing Transferability in Graph Foundation Models for Text-Attributed Graphs.

Yun Zhu, Haizhou Shi, Xiaotang Wang, Yongchao Liu, Yaoke Wang, Boci Peng, Chuntao Hong, Siliang Tang

Proceedings of the ACM on Web Conference 2025, 2025

Transferable and Forecastable User Targeting Foundation Model.

Bin Dou, Baokun Wang, Yun Zhu, Xiaotong Lin, Yike Xu, Xiaorui Huang, Yang Chen, Yun Liu, Shaoshuai Han, Yongchao Liu, Tianyi Zhang, Yu Cheng, Weiqiang Wang, Chuntao Hong

Proceedings of the Companion Proceedings of the ACM on Web Conference 2025, 2025

Graph Triple Attention Networks: A Decoupled Perspective.

Xiaotang Wang, Yun Zhu, Haizhou Shi, Yongchao Liu, Chuntao Hong

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.1, 2025

Multi-Grained Preference Enhanced Transformer for Multi-Behavior Sequential Recommendation.

Chuan He, Yongchao Liu, Qiang Li, Weiqiang Wang, Xing Fu, Xinyi Fu, Chuntao Hong, Xinwei Yao

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.2, 2025

TeMatch: A Fast Temporal Subgraph Matching Framework with Temporal-Aware Subgraph Matching Algorithms.

Chengying Huan, Heng Zhang, Yongchao Liu, Likang Chen, Xuran Wang, Yongchun Jiang, Shaonan Ma, Yanjun Wu

Proceedings of the 41st IEEE International Conference on Data Engineering, 2025

M³GQA: A Multi-Entity Multi-Hop Multi-Setting Graph Question Answering Benchmark.

Boci Peng, Yongchao Liu, Xiaohe Bo, Jiaxin Guo, Yun Zhu, Xuanbo Fan, Chuntao Hong, Yan Zhang

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024

TeGraph+: Scalable Temporal Graph Processing Enabling Flexible Edge Modifications.

Chengying Huan, Yongchao Liu, Heng Zhang, Hang Liu, Shiyang Chen, Shuaiwen Leon Song, Yanjun Wu

IEEE Trans. Parallel Distributed Syst., August, 2024

<i>TEA+</i>: A Novel Temporal Graph Random Walk Engine with Hybrid Storage Architecture.

Chengying Huan, Yongchao Liu, Heng Zhang, Shuaiwen Song, Santosh Pandey, Shiyang Chen, Xiangfei Fang, Yue Jin, Baptiste Lepers, Yanjun Wu, Hang Liu

ACM Trans. Archit. Code Optim., June, 2024

Multi-Grained Preference Enhanced Transformer for Multi-Behavior Sequential Recommendation.

Chuan He, Yongchao Liu, Qiang Li, Weiqiang Wang, Xin Fu, Xinyi Fu, Chuntao Hong, Xin Yao

CoRR, 2024

CL4KGE: A Curriculum Learning Method for Knowledge Graph Embedding.

Yang Liu, Chuan Zhou, Peng Zhang, Yanan Cao, Yongchao Liu, Zhao Li, Hongyang Chen

CoRR, 2024

Graph Retrieval-Augmented Generation: A Survey.

Boci Peng, Yun Zhu, Yongchao Liu, Xiaohe Bo, Haizhou Shi, Chuntao Hong, Yan Zhang, Siliang Tang

CoRR, 2024

Graph Triple Attention Network: A Decoupled Perspective.

Xiaotang Wang, Yun Zhu, Haizhou Shi, Yongchao Liu, Chuntao Hong

CoRR, 2024

UniGAP: A Universal and Adaptive Graph Upsampling Approach to Mitigate Over-Smoothing in Node Classification Tasks.

Xiaotang Wang, Yun Zhu, Haizhou Shi, Yongchao Liu, Chuntao Hong

CoRR, 2024

GraphRPM: Risk Pattern Mining on Industrial Large Attributed Graphs.

Sheng Tian, Xintan Zeng, Yifei Hu, Baokun Wang, Yongchao Liu, Yue Jin, Changhua Meng, Chuntao Hong, Tianyi Zhang, Weiqiang Wang

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track, 2024

Subgraph Retrieval Enhanced by Graph-Text Alignment for Commonsense Question Answering.

Boci Peng, Yongchao Liu, Xiaohe Bo, Sheng Tian, Baokun Wang, Chuntao Hong, Yan Zhang

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024

DiVerFed: Distribution-Aware Vertical Federated Learning for Missing Information.

Pengyu Qiu, Yongchao Liu, Xintan Zeng

Proceedings of the Knowledge Science, Engineering and Management, 2024

Integer Is Enough: When Vertical Federated Learning Meets Rounding.

Pengyu Qiu, Yuwen Pu, Yongchao Liu, Wenyan Liu, Yun Yue, Xiaowei Zhu, Lichun Li, Jinbao Li, Shouling Ji

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

2023

Multi-Aspect Heterogeneous Graph Augmentation.

Yuchen Zhou, Yanan Cao, Yongchao Liu, Yanmin Shang, Peng Zhang, Zheng Lin, Yun Yue, Baokun Wang, Xing Fu, Weiqiang Wang

Proceedings of the ACM Web Conference 2023, 2023

Sharpness-Aware Minimization Revisited: Weighted Sharpness as a Regularization Term.

Yun Yue, Jiadi Jiang, Zhiling Ye, Ning Gao, Yongchao Liu, Ke Zhang

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

TEA: A General-Purpose Temporal Graph Random Walk Engine.

Chengying Huan, Shuaiwen Leon Song, Santosh Pandey, Hang Liu, Yongchao Liu, Baptiste Lepers, Changhua He, Kang Chen, Jinlei Jiang, Yongwei Wu

Proceedings of the Eighteenth European Conference on Computer Systems, 2023

FAF: A Risk Detection Framework on Industry-Scale Graphs.

Yice Luo, Guannan Wang, Yongchao Liu, Jiaxin Yue, Weihong Cheng, Binjie Fei

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

G-Sparse: Compiler-Driven Acceleration for Generalized Sparse Computation for Graph Neural Networks on Modern GPUs.

Yue Jin, Chengying Huan, Heng Zhang, Yongchao Liu, Shuaiwen Leon Song, Rui Zhao, Yao Zhang, Changhua He, Wenguang Chen

Proceedings of the 32nd International Conference on Parallel Architectures and Compilation Techniques, 2023

2022

Bring orders into uncertainty: enabling efficient uncertain graph processing via novel path sampling on multi-accelerator systems.

Heng Zhang, Lingda Li, Hang Liu, Donglin Zhuang, Rui Liu, Chengying Huan, Shuang Song, Dingwen Tao, Yongchao Liu, Charles He, Yanjun Wu, Shuaiwen Leon Song

Proceedings of the ICS '22: 2022 International Conference on Supercomputing, Virtual Event, June 28, 2022

TeGraph: A Novel General-Purpose Temporal Graph Computing Engine.

Chengying Huan, Hang Liu, Mengxing Liu, Yongchao Liu, Changhua He, Kang Chen, Jinlei Jiang, Yongwei Wu, Shuaiwen Leon Song

Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

T-GCN: A Sampling Based Streaming Graph Neural Network System with Hybrid Architecture.

Chengying Huan, Shuaiwen Leon Song, Yongchao Liu, Heng Zhang, Hang Liu, Charles He, Kang Chen, Jinlei Jiang, Yongwei Wu

Proceedings of the International Conference on Parallel Architectures and Compilation Techniques, 2022

2021

Taking the Pulse of Financial Activities with Online Graph Processing.

Xiaowei Zhu, Zhisong Fu, Zhenxuan Pan, Jin Jiang, Chuntao Hong, Yongchao Liu, Yang Fang, Wenguang Chen, Changhua He

ACM SIGOPS Oper. Syst. Rev., 2021

Path-based Deep Network for Candidate Item Matching in Recommenders.

Houyi Li, Zhihong Chen, Chenliang Li, Rong Xiao, Hongbo Deng, Peng Zhang, Yongchao Liu, Haihong Tang

Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

Adaptive Optimizers with Sparse Group Lasso for Neural Networks in CTR Prediction.

Yun Yue, Yongchao Liu, Suo Tong, Minghao Li, Zhen Zhang, Chunyang Wen, Huanjun Bao, Lihong Gu, Jinjie Gu, Yixiang Mu

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Heterogeneous Graph Neural Architecture Search.

Yang Gao, Peng Zhang, Zhao Li, Chuan Zhou, Yongchao Liu, Yue Hu

Proceedings of the IEEE International Conference on Data Mining, 2021

2019

Kmerind: A Flexible Parallel Library for K-mer Indexing of Biological Sequences on Distributed Memory Systems.

Tony Pan, Patrick Flick, Chirag Jain, Yongchao Liu, Srinivas Aluru

IEEE ACM Trans. Comput. Biol. Bioinform., 2019

2018

LightSpMV: Faster CUDA-Compatible Sparse Matrix-Vector Multiplication Using Compressed Sparse Rows.

Yongchao Liu, Bertil Schmidt

J. Signal Process. Syst., 2018

2017

Parallelized Kendall's Tau Coefficient Computation via SIMD Vectorized Sorting On Many-Integrated-Core Processors.

Yongchao Liu, Tony Pan, Oded Green, Srinivas Aluru

CoRR, 2017

A greedy alignment-free distance estimator for phylogenetic inference.

Sharma V. Thankachan, Sriram P. Chockalingam, Yongchao Liu, Ambujam Krishnan, Srinivas Aluru

BMC Bioinform., 2017

AFS: identification and quantification of species composition by metagenomic sequencing.

Yongchao Liu, Fabian Ripp, Rene Koeppel, Hanno Schmidt, Sören Lukas Hellmann, Mathias Weber, Christopher Felix Krombholz, Bertil Schmidt, Thomas Hankeln

Bioinform., 2017

SWhybrid: A Hybrid-Parallel Framework for Large-Scale Protein Sequence Database Search.

Haidong Lan, Weiguo Liu, Yongchao Liu, Bertil Schmidt

Proceedings of the 2017 IEEE International Parallel and Distributed Processing Symposium, 2017

PUNAS: A Parallel Ungapped-Alignment-Featured Seed Verification Algorithm for Next-Generation Sequencing Read Alignment.

Yuandong Chan, Kai Xu, Haidong Lan, Weiguo Liu, Yongchao Liu, Bertil Schmidt

Proceedings of the 2017 IEEE International Parallel and Distributed Processing Symposium, 2017

CUSHAW Suite: Parallel and Efficient Algorithms for NGS Read Alignment.

Yongchao Liu, Bertil Schmidt

Proceedings of the Algorithms for Next-Generation Sequencing Data, Techniques, 2017

2016

Parallel and Space-Efficient Construction of Burrows-Wheeler Transform and Suffix Array for Big Genome Data.

Yongchao Liu, Thomas Hankeln, Bertil Schmidt

IEEE ACM Trans. Comput. Biol. Bioinform., 2016

Bit-parallel approximate pattern matching: Kepler GPU versus Xeon Phi.

Tuan Tu Tran, Yongchao Liu, Bertil Schmidt

Parallel Comput., 2016

ALFRED: A Practical Method for Alignment-Free Distance Computation.

Sharma V. Thankachan, Sriram P. Chockalingam, Yongchao Liu, Alberto Apostolico, Srinivas Aluru

J. Comput. Biol., 2016

LightScan: Faster Scan Primitive on CUDA Compatible Manycore Processors.

Yongchao Liu, Srinivas Aluru

CoRR, 2016

SNVSniffer: an integrated caller for germline and somatic single-nucleotide and indel mutations.

Yongchao Liu, Martin Loewer, Srinivas Aluru, Bertil Schmidt

BMC Syst. Biol., 2016

MSAProbs-MPI: parallel multiple sequence aligner for distributed-memory systems.

Jorge González-Domínguez, Yongchao Liu, Juan Touriño, Bertil Schmidt

Bioinform., 2016

Parallel Pairwise Correlation Computation on Intel Xeon Phi Clusters.

Yongchao Liu, Tony Pan, Srinivas Aluru

Proceedings of the 28th International Symposium on Computer Architecture and High Performance Computing, 2016

2015

GSWABE: faster GPU-accelerated sequence alignment with optimal alignment retrieval for short DNA sequences.

Yongchao Liu, Bertil Schmidt

Concurr. Comput. Pract. Exp., 2015

A greedy alignment-free distance estimator for phylogenetic inference (extended abstract).

Sharma V. Thankachan, Sriram P. Chockalingam, Yongchao Liu, Ambujam Krishnan, Srinivas Aluru

Proceedings of the 5th IEEE International Conference on Computational Advances in Bio and Medical Sciences, 2015

SNVSniffer: An integrated caller for germline and somatic SNVs based on Bayesian models.

Yongchao Liu, Martin Loewer, Srinivas Aluru, Bertil Schmidt

Proceedings of the 2015 IEEE International Conference on Bioinformatics and Biomedicine, 2015

LightSpMV: Faster CSR-based sparse matrix-vector multiplication on CUDA-enabled GPUs.

Yongchao Liu, Bertil Schmidt

Proceedings of the 26th IEEE International Conference on Application-specific Systems, 2015

2014

CUSHAW2-GPU: Empowering Faster Gapped Short-Read Alignment Using GPU Computing.

Yongchao Liu, Bertil Schmidt

IEEE Des. Test, 2014

HECTOR: a parallel multistage homopolymer spectrum based error corrector for 454 sequencing data.

Adrianto Wirawan, Robert S. Harris, Yongchao Liu, Bertil Schmidt, Jan Schröder

BMC Bioinform., 2014

Bit-Parallel Approximate Pattern Matching on the Xeon Phi Coprocessor.

Tuan Tu Tran, Simon Schindel, Yongchao Liu, Bertil Schmidt

Proceedings of the 26th IEEE International Symposium on Computer Architecture and High Performance Computing, 2014

SWAPHI-LS: Smith-Waterman Algorithm on Xeon Phi coprocessors for Long DNA Sequences.

Yongchao Liu, Tuan Tu Tran, Felix Lauenroth, Bertil Schmidt

Proceedings of the 2014 IEEE International Conference on Cluster Computing, 2014

SWAPHI: Smith-waterman protein database search on Xeon Phi coprocessors.

Yongchao Liu, Bertil Schmidt

Proceedings of the IEEE 25th International Conference on Application-Specific Systems, 2014

2013

CUDASW++ 3.0: accelerating Smith-Waterman protein database search by coupling CPU and GPU SIMD instructions.

Yongchao Liu, Adrianto Wirawan, Bertil Schmidt

BMC Bioinform., 2013

Musket: a multistage <i>k-</i>mer spectrum-based error corrector for Illumina sequence data.

Yongchao Liu, Jan Schröder, Bertil Schmidt

Bioinform., 2013

Faster GPU-Accelerated Smith-Waterman Algorithm with Alignment Backtracking for Short DNA Sequences.

Yongchao Liu, Bertil Schmidt

Proceedings of the Parallel Processing and Applied Mathematics, 2013

2012

CUSHAW: a CUDA compatible short read aligner to large genomes based on the Burrows-Wheeler transform.

Yongchao Liu, Bertil Schmidt, Douglas L. Maskell

Bioinform., 2012

Long read alignment based on maximal exact match seeds.

Yongchao Liu, Bertil Schmidt

Bioinform., 2012

Evaluation of GPU-based Seed Generation for Computational Genomics Using Burrows-Wheeler Transform.

Yongchao Liu, Bertil Schmidt

Proceedings of the 26th IEEE International Parallel and Distributed Processing Symposium Workshops & PhD Forum, 2012

2011

Parallelized short read assembly of large genomes using de Bruijn graphs.

Yongchao Liu, Bertil Schmidt, Douglas L. Maskell

BMC Bioinform., 2011

DecGPU: distributed error correction on massively parallel graphics processing units using CUDA and MPI.

Yongchao Liu, Bertil Schmidt, Douglas L. Maskell

BMC Bioinform., 2011

CompleteMOTIFs: DNA motif discovery platform for transcription factor binding experiments.

Lakshmi Kuttippurathu, Michael Hsing, Yongchao Liu, Bertil Schmidt, Douglas L. Maskell, Kyungjoon Lee, Aibin He, William T. Pu, Sek Won Kong

Bioinform., 2011

An Ultrafast Scalable Many-Core Motif Discovery Algorithm for Multiple GPUs.

Yongchao Liu, Bertil Schmidt, Douglas L. Maskell

Proceedings of the 25th IEEE International Symposium on Parallel and Distributed Processing, 2011

Mapping of BLASTP Algorithm onto GPU Clusters.

Weiguo Liu, Bertil Schmidt, Yongchao Liu, Gerrit Voss, Wolfgang Müller-Wittig

Proceedings of the 17th IEEE International Conference on Parallel and Distributed Systems, 2011

2010

CUDA-MEME: Accelerating motif discovery in biological sequences using CUDA-enabled graphics processing units.

Yongchao Liu, Bertil Schmidt, Weiguo Liu, Douglas L. Maskell

Pattern Recognit. Lett., 2010

MSAProbs: multiple sequence alignment based on pair hidden Markov models and partition function posterior probabilities.

Yongchao Liu, Bertil Schmidt, Douglas L. Maskell

Bioinform., 2010

2009

Parallel reconstruction of neighbor-joining trees for large multiple sequence alignments using CUDA.

Yongchao Liu, Bertil Schmidt, Douglas L. Maskell

Proceedings of the 23rd IEEE International Symposium on Parallel and Distributed Processing, 2009

MSA-CUDA: Multiple Sequence Alignment on Graphics Processing Units with CUDA.

Yongchao Liu, Bertil Schmidt, Douglas L. Maskell

Proceedings of the 20th IEEE International Conference on Application-Specific Systems, 2009