Agent-Based Web Service Composition with JADE and JXTA. - Shenghua Liu; Peep Küngas; Mihhail Matskin (SWWS, 2006)

Topological routing to maximize routability for package substrate. - Shenghua Liu; Guoqiang Chen; Tom Tong Jing; Lei He 001; Tianpei Zhang; Robi Dutta; Xianlong Hong (DAC, 2008)

Diffusion-driven congestion reduction for substrate topological routing. - Shenghua Liu; Guoqiang Chen; Tom Tong Jing; Lei He 001; Robi Dutta; Xianlong Hong (ISPD, 2009)

Substrate Topological Routing for High-Density Packages. - Shenghua Liu; Guoqiang Chen; Tom Tong Jing; Lei He 001; Tianpei Zhang; Robi Dutta; Xianlong Hong (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2009)

Simultaneous slack budgeting and retiming for synchronous circuits optimization. - Shenghua Liu; Yuchun Ma; Xianlong Hong; Yu Wang 002 (ASP-DAC, 2010)

Effective congestion reduction for IC package substrate routing. - Shenghua Liu; Guoqiang Chen; Tom Tong Jing; Lei He 001; Robi Dutta; Xianlong Hong (ACM Trans. Design Autom. Electr. Syst., 2010)

ICTNET at Microblog Track TREC 2011. - Peng Cao; Jinhua Gao; Yubao Yu; Shenghua Liu; Yue Liu; Xueqi Cheng (TREC, 2011)

Clustering short text using Ncut-weighted non-negative matrix factorization. - Xiaohui Yan; Jiafeng Guo; Shenghua Liu; Xueqi Cheng; Yanfeng Wang (CIKM, 2012)

Using WordNet-Based Neighborhood for Improving Social Tag Recommendation. - Ya-Tao Zhu; Shenghua Liu; Xueqi Cheng; Yue Liu; Yuanzhuo Wang; Jin-Gang Liu (ICIC (2), 2012)

Finding Topic-Related Tweets Using Conversational Thread. - Peng Cao; Shenghua Liu; Jinhua Gao; Huawei Shen; Jingyuan Li; Yue Liu; Xueqi Cheng (IIP, 2012)

ICTNET at Microblog Track TREC 2012. - Bolong Zhu; Jinghua Gao; Xiao Han; Cunhui Shi; Shenghua Liu; Yue Liu; Xueqi Cheng (TREC, 2012)

Adaptive co-training SVM for sentiment classification on tweets. - Shenghua Liu; Fuxin Li; Fangtao Li; Xueqi Cheng; Huawei Shen (CIKM, 2013)

Learning Topics in Short Texts by Non-negative Matrix Factorization on Term Correlation Matrix. - Xueqi Cheng; Jiafeng Guo; Shenghua Liu; Yanfeng Wang; Xiaohui Yan (SDM, 2013)

ICTNET at Microblog Track in TREC 2013. - Jinhua Gao; Guoxin Cui; Shenghua Liu; Yue Liu; Xueqi Cheng (TREC, 2013)

A Blending Method for Automated Social Tagging. - Shenghua Liu; Ya-Tao Zhu; Jiafeng Guo; Yuanzhuo Wang; Xueqi Cheng (Web Intelligence, 2013)

Co-training and visualizing sentiment evolvement for tweet events. - Shenghua Liu; Wenjun Zhu; Ning Xu 006; Fangtao Li; Xueqi Cheng; Yue Liu; Yuanzhuo Wang (WWW (Companion Volume), 2013)

SUIT: A Supervised User-Item Based Topic Model for Sentiment Analysis. - Fangtao Li; Sheng Wang 012; Shenghua Liu; Ming Zhang 004 (AAAI, 2014)

Ranking Tweets by Labeled and Collaboratively Selected Pairs with Transitive Closure. - Shenghua Liu; Xueqi Cheng; Fangtao Li (AAAI, 2014)

Ranking Tweets with Local and Global Consistency Using Rich Features. - Zhankun Huang; Shenghua Liu; Pan Du; Xueqi Cheng (PAKDD (1), 2014)

Learning User-Specific Latent Influence and Susceptibility from Information Cascades. - Yongqing Wang 005; Huawei Shen; Shenghua Liu; Xueqi Cheng (AAAI, 2015)

TASC: Topic-Adaptive Sentiment Classification on Dynamic Tweets. - Shenghua Liu; Xueqi Cheng; Fuxin Li; Fangtao Li (IEEE Trans. Knowl. Data Eng., 2015)

Predict Anchor Links across Social Networks via an Embedding Approach. - Tong Man; Huawei Shen; Shenghua Liu; Xiaolong Jin 001; Xueqi Cheng (IJCAI, 2016)

Modeling and Predicting Retweeting Dynamics via a Mixture Process. - Jinhua Gao; Huawei Shen; Shenghua Liu; Xueqi Cheng (WWW (Companion Volume), 2016)

Learning Sentimental Influences from Users' Behaviors. - Shenghua Liu; Houdong Zheng; Huawei Shen; Xiangwen Liao; Xueqi Cheng (CoRR, 2016)

HoloScope: Topology-and-Spike Aware Fraud Detection. - Shenghua Liu; Bryan Hooi; Christos Faloutsos (CIKM, 2017)

EyeQual: Accurate, Explainable, Retinal Image Quality Assessment. - Pedro Costa 005; Aurélio J. C. Campilho; Bryan Hooi; Asim Smailagic; Kris Kitani; Shenghua Liu; Christos Faloutsos; Adrian Galdran (ICMLA, 2017)

Learning Concise Representations of Users' Influences through Online Behaviors. - Shenghua Liu; Houdong Zheng; Huawei Shen; Xueqi Cheng; Xiangwen Liao (IJCAI, 2017)

Cascade Dynamics Modeling with Attention-based Recurrent Neural Network. - Yongqing Wang 005; Huawei Shen; Shenghua Liu; Jinhua Gao; Xueqi Cheng (IJCAI, 2017)

Single-Pass PCA of Large High-Dimensional Data. - Wenjian Yu; Yu Gu; Jian Li; Shenghua Liu; Yaohang Li (IJCAI, 2017)

Personalized Ranking Recommendation via Integrating Multiple Feedbacks. - Jian Liu 001; Chuan Shi 001; Binbin Hu; Shenghua Liu; Philip S. Yu (PAKDD (2), 2017)

Marked Temporal Dynamics Modeling Based on Recurrent Neural Network. - Yongqing Wang 005; Shenghua Liu; Huawei Shen; Jinhua Gao; Xueqi Cheng (PAKDD (1), 2017)

BeatLex: Summarizing and Forecasting Time Series with Patterns. - Bryan Hooi; Shenghua Liu; Asim Smailagic; Christos Faloutsos (ECML/PKDD (2), 2017)

Marked Temporal Dynamics Modeling based on Recurrent Neural Network. - Yongqing Wang 005; Shenghua Liu; Huawei Shen; Xueqi Cheng (CoRR, 2017)

EagleMine: Vision-Guided Mining in Large Graphs. - Wenjie Feng 001; Shenghua Liu; Christos Faloutsos; Bryan Hooi; Huawei Shen; Xueqi Cheng (CoRR, 2017)

NeuCast: Seasonal Neural Forecast of Power Grid Time Series. - Pudi Chen; Shenghua Liu; Chuan Shi 001; Bryan Hooi; Bai Wang 001; Xueqi Cheng (IJCAI, 2018)

MFPR: A Personalized Ranking Recommendation with Multiple Feedback. - Chuan Shi 001; Jian Liu 001; Yiding Zhang; Binbin Hu; Shenghua Liu; Philip S. Yu (ACM Trans. Soc. Comput., 2018)

Optimal Algorithm for Profiling Dynamic Arrays with Finite Values. - Dingcheng Yang; Wenjian Yu; Junhui Deng; Shenghua Liu (EDBT, 2019)

BeatGAN: Anomalous Rhythm Detection using Adversarially Generated Time Series. - Bin Zhou; Shenghua Liu; Bryan Hooi; Xueqi Cheng; Jing Ye (IJCAI, 2019)

Beyond Outliers and on to Micro-clusters: Vision-Guided Anomaly Detection. - Wenjie Feng 001; Shenghua Liu; Christos Faloutsos; Bryan Hooi; Huawei Shen; Xueqi Cheng (PAKDD (1), 2019)

EigenPulse: Detecting Surges in Large Streaming Graphs with Row Augmentation. - Jiabao Zhang; Shenghua Liu; Wenjian Yu; Wenjie Feng 001; Xueqi Cheng (PAKDD (2), 2019)

CatchCore: Catching Hierarchical Dense Subtensor. - Wenjie Feng 001; Shenghua Liu; Xueqi Cheng (ECML/PKDD (1), 2019)

SMF: Drift-Aware Matrix Factorization with Seasonal Patterns. - Bryan Hooi; Kijung Shin; Shenghua Liu; Christos Faloutsos (SDM, 2019)

CT LIS: Learning Influences and Susceptibilities through Temporal Behaviors. - Shenghua Liu; Huawei Shen; Houdong Zheng; Xueqi Cheng; Xiangwen Liao (ACM Trans. Knowl. Discov. Data, 2019)

A Contrast Metric for Fraud Detection in Rich Graphs. - Shenghua Liu; Bryan Hooi; Christos Faloutsos (IEEE Trans. Knowl. Data Eng., 2019)

FlowScope: Spotting Money Laundering Based on Graphs. - Xiangfeng Li; Shenghua Liu; Zifeng Li; Xiaotian Han; Chuan Shi 001; Bryan Hooi; He Huang; Xueqi Cheng (AAAI, 2020)

Provably Robust Node Classification via Low-Pass Message Passing. - Yiwei Wang 001; Shenghua Liu; Minji Yoon; Hemank Lamba; Wei Wang 059; Christos Faloutsos; Bryan Hooi (ICDM, 2020)

Efficient Model-Based Collaborative Filtering with Fast Adaptive PCA. - Xiangyun Ding; Wenjian Yu; Yuyang Xie; Shenghua Liu (ICTAI, 2020)

Silicon-Based Integrated Broadband Wavelength-Meter with Low Temperature Sensitivity. - Long Chen 013; Chris Doerr 001; Shenghua Liu; Li Chen; Michelle Xu (OFC, 2020)

SpecGreedy: Unified Dense Subgraph Detection. - Wenjie Feng 001; Shenghua Liu; Danai Koutra; Huawei Shen; Xueqi Cheng (ECML/PKDD (1), 2020)

Summarizing graphs using the configuration model. - Houquan Zhou 002; Shenghua Liu; Kyuhan Lee; Kijung Shin; Huawei Shen; Xueqi Cheng (CoRR, 2020)

AugSplicing: Synchronized Behavior Detection in Streaming Tensors. - Jiabao Zhang; Shenghua Liu; Wenting Hou; Siddharth Bhatia 001; Huawei Shen; Wenjian Yu; Xueqi Cheng (AAAI, 2021)

CubeFlow: Money Laundering Detection with Coupled Tensors. - Xiaobing Sun; Jiabao Zhang; Qiming Zhao; Shenghua Liu; Jinglei Chen; Ruoyu Zhuang; Huawei Shen; Xueqi Cheng (PAKDD (1), 2021)

DPGS: Degree-Preserving Graph Summarization. - Houquan Zhou 002; Shenghua Liu; Kyuhan Lee; Kijung Shin; Huawei Shen; Xueqi Cheng (SDM, 2021)

EagleMine: Vision-guided Micro-clusters recognition and collective anomaly detection. - Wenjie Feng 001; Shenghua Liu; Christos Faloutsos; Bryan Hooi; Huawei Shen; Xueqi Cheng (Future Gener. Comput. Syst., 2021)

Integrating a prospect theory-based consensus-reaching process into large-scale quality function deployment and its application in the evaluation of contingency plan. - Yan Zhu; Chuanhao Fan; Jing Xiao; Shenghua Liu (J. Intell. Fuzzy Syst., 2021)

MonLAD: Money Laundering Agents Detection in Transaction Streams. - Xiaobing Sun; Wenjie Feng 001; Shenghua Liu; Yuyang Xie; Siddharth Bhatia 001; Bryan Hooi; Wenhan Wang; Xueqi Cheng (WSDM, 2022)

On the Cybernetics of Crowdsourcing Innovation: A Process Model. - Lei Lin; Huawei Shen; Shenghua Liu; Easton Li Xu; Xueqi Cheng (IEEE Access, 2022)

Multi-scale Anomaly Detection for Big Time Series of Industrial Sensors. - Quan Ding; Shenghua Liu; Bin Zhou; Huawei Shen; Xueqi Cheng (CoRR, 2022)

Learning node embeddings via summary graphs: a brief theoretical analysis. - Houquan Zhou 002; Shenghua Liu; Danai Koutra; Huawei Shen; Xueqi Cheng (CoRR, 2022)

CGCNImp: a causal graph convolutional network for multivariate time series imputation. - Caizheng Liu; Guangfan Cui; Shenghua Liu (PeerJ Comput. Sci., 2022)

A Provable Framework of Learning Graph Embeddings via Summarization. - Houquan Zhou 002; Shenghua Liu; Danai Koutra; Huawei Shen; Xueqi Cheng (AAAI, 2023)

W3Detector: Detecting Fraudulent Online Sellers Based on Temporal and Spacial Information. - Shengbo Tong; Yuyang Xie; Shenghua Liu; Wenjian Yu; Jixuan Cai (ICMLA, 2023)

Fast Searching The Densest Subgraph And Decomposition With Local Optimality. - Yugao Zhu; Shenghua Liu; Wenjie Feng 001; Xueqi Cheng (CoRR, 2023)

Time Series Anomaly Detection With Adversarial Reconstruction Networks. - Shenghua Liu; Bin Zhou; Quan Ding; Bryan Hooi; Zhengbo Zhang; Huawei Shen; Xueqi Cheng (IEEE Trans. Knowl. Data Eng., 2023)

Hierarchical Dense Pattern Detection in Tensors. - Wenjie Feng 001; Shenghua Liu; Xueqi Cheng (ACM Trans. Knowl. Discov. Data, 2023)

A Minimum Cost Consensus-Based Failure Mode and Effect Analysis Framework Considering Experts' Limited Compromise and Tolerance Behaviors. - Hengjie Zhang; Shenghua Liu; Yucheng Dong; Francisco Chiclana; Enrique Herrera-Viedma (IEEE Trans. Cybern., 2023)

LPNL: Scalable Link Prediction with Large Language Models. - Baolong Bi; Shenghua Liu; Yiwei Wang 001; Lingrui Mei; Xueqi Cheng (ACL (Findings), 2024)

Adaptive Token Biaser: Knowledge Editing via Biasing Key Entities. - Baolong Bi; Shenghua Liu; Yiwei Wang 001; Lingrui Mei; Hongcheng Gao; Yilong Xu; Xueqi Cheng (EMNLP (Findings), 2024)

SLANG: New Concept Comprehension of Large Language Models. - Lingrui Mei; Shenghua Liu; Yiwei Wang 001; Baolong Bi; Xueqi Cheng (EMNLP, 2024)

Graph Summarization for Preserving Spectral Characteristics. - Houquan Zhou 002; Shenghua Liu; Huawei Shen; Xueqi Cheng (SDM, 2024)

SLANG: New Concept Comprehension of Large Language Models. - Lingrui Mei; Shenghua Liu; Yiwei Wang 001; Baolong Bi; Xueqi Chen (CoRR, 2024)

Scalable Link Prediction on Large-Scale Heterogeneous Graphs with Large Language Models. - Baolong Bi; Shenghua Liu; Yiwei Wang 001; Lingrui Mei; Xueqi Chen (CoRR, 2024)

Graph Descriptive Order Improves Reasoning with Large Language Model. - Yuyao Ge; Shenghua Liu; Wenjie Feng 001; Lingrui Mei; Lizhe Chen; Xueqi Cheng (CoRR, 2024)

Is Factuality Decoding a Free Lunch for LLMs? Evaluation on Knowledge Editing Benchmark. - Baolong Bi; Shenghua Liu; Yiwei Wang 001; Lingrui Mei; Xueqi Cheng (CoRR, 2024)

Decoding by Contrasting Knowledge: Enhancing LLMs' Confidence on Edited Facts. - Baolong Bi; Shenghua Liu; Lingrui Mei; Yiwei Wang 001; Pengliang Ji; Xueqi Cheng (CoRR, 2024)

StruEdit: Structured Outputs Enable the Fast and Accurate Knowledge Editing for Large Language Models. - Baolong Bi; Shenghua Liu; Yiwei Wang 001; Lingrui Mei; Hongcheng Gao; Junfeng Fang; Xueqi Cheng (CoRR, 2024)

HiddenGuard: Fine-Grained Safe Generation with Specialized Representation Router. - Lingrui Mei; Shenghua Liu; Yiwei Wang 001; Baolong Bi; Ruibin Yuan; Xueqi Cheng (CoRR, 2024)

Unified Dense Subgraph Detection: Fast Spectral Theory Based Algorithms. - Wenjie Feng 001; Shenghua Liu; Danai Koutra; Xueqi Cheng (IEEE Trans. Knowl. Data Eng., 2024)

Node Embedding Preserving Graph Summarization. - Houquan Zhou 002; Shenghua Liu; Huawei Shen; Xueqi Cheng (ACM Trans. Knowl. Discov. Data, 2024)

Interrelated Dense Pattern Detection in Multilayer Networks. - Wenjie Feng 001; Li Wang 142; Bryan Hooi; See-Kiong Ng; Shenghua Liu (IEEE Trans. Knowl. Data Eng., 2024)

Context-DPO: Aligning Language Models for Context-Faithfulness. - Baolong Bi; Shaohan Huang; Yiwei Wang 001; Tianchi Yang; Zihan Zhang; Haizhen Huang; Lingrui Mei; Junfeng Fang; Zehao Li; Furu Wei; Weiwei Deng; Feng Sun 008; et al. (ACL (Findings), 2025)

Decoding by Contrasting Knowledge: Enhancing Large Language Model Confidence on Edited Facts. - Baolong Bi; Shenghua Liu; Lingrui Mei; Yiwei Wang 001; Junfeng Fang; Pengliang Ji; Xueqi Cheng (ACL (1), 2025)

Can Graph Descriptive Order Affect Solving Graph Problems with LLMs? - Yuyao Ge; Shenghua Liu; Baolong Bi; Yiwei Wang 001; Lingrui Mei; Wenjie Feng 001; Lizhe Chen; Xueqi Cheng (ACL (1), 2025)

"Not Aligned" is Not "Malicious": Being Careful about Hallucinations of Large Language Models' Jailbreak. - Lingrui Mei; Shenghua Liu; Yiwei Wang 001; Baolong Bi; Jiayi Mao; Xueqi Cheng (COLING, 2025)

Is Factuality Enhancement a Free Lunch For LLMs? Better Factuality Can Lead to Worse Context-Faithfulness. - Baolong Bi; Shenghua Liu; Yiwei Wang 001; Lingrui Mei; Junfeng Fang; Hongcheng Gao; Shiyu Ni; Xueqi Cheng (ICLR, 2025)

Addressing the influence of limited tolerance and compromise behaviors on the social trust network consensus-reaching process. - Hengjie Zhang; Shenghua Liu; Cong-Cong Li; Yucheng Dong; Francisco Chiclana; Enrique Herrera-Viedma (Inf. Sci., 2025)

Parameters vs. Context: Fine-Grained Control of Knowledge Reliance in Language Models. - Baolong Bi; Shenghua Liu; Yiwei Wang 001; Yilong Xu; Junfeng Fang; Lingrui Mei; Xueqi Cheng (CoRR, 2025)

Innate Reasoning is Not Enough: In-Context Learning Enhances Reasoning Large Language Models with Less Overthinking. - Yuyao Ge; Shenghua Liu; Yiwei Wang 001; Lingrui Mei; Lizhe Chen; Baolong Bi; Xueqi Cheng (CoRR, 2025)

a1: Steep Test-time Scaling Law via Environment Augmented Generation. - Lingrui Mei; Shenghua Liu; Yiwei Wang 001; Baolong Bi; Yuyao Ge; Jun Wan; Yurong Wu; Xueqi Cheng (CoRR, 2025)

Who is in the Spotlight: The Hidden Bias Undermining Multimodal Retrieval-Augmented Generation. - Jiayu Yao; Shenghua Liu; Yiwei Wang 001; Lingrui Mei; Baolong Bi; Yuyao Ge; Zhecheng Li; Xueqi Cheng (CoRR, 2025)

Rethinking All Evidence: Enhancing Trustworthy Retrieval-Augmented Generation via Conflict-Driven Summarization. - Juan Chen; Baolong Bi; Wei Zhang; Jingyan Sui; Xiaofei Zhu; Yuanzhuo Wang; Lingrui Mei; Shenghua Liu (CoRR, 2025)

RefineX: Learning to Refine Pre-training Data at Scale from Expert-Guided Programs. - Baolong Bi; Shenghua Liu; Xingzhang Ren; Dayiheng Liu; Junyang Lin; Yiwei Wang 001; Lingrui Mei; Junfeng Fang; Jiafeng Guo; Xueqi Cheng (CoRR, 2025)

A Survey of Context Engineering for Large Language Models. - Lingrui Mei; Jiayu Yao; Yuyao Ge; Yiwei Wang 001; Baolong Bi; Yujun Cai; Jiazhi Liu; Mingyu Li; Zhong-Zhi Li; Duzhen Zhang; Chenlin Zhou; Jiayi Mao; et al. (CoRR, 2025)