Publications

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

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

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

Lingrui Mei, Shenghua Liu, Yiwei Wang, Baolong Bi, Jiayi Mao, Xueqi Cheng (2025). \"Not Aligned\" is Not \"Malicious\": Being Careful about Hallucinations of Large Language Models' Jailbreak. Proceedings of the 31st International Conference on Computational Linguistics, COLING 2025, Abu Dhabi, UAE, January 19-24, 2025.

Yuyao Ge, Shenghua Liu, Baolong Bi, Yiwei Wang, Lingrui Mei, Wenjie Feng, Lizhe Chen, Xueqi Cheng (2024). Can Graph Descriptive Order Affect Solving Graph Problems with LLMs?. Association for Computational Linguistics (ACL) Main, 2025.

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

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

Lingrui Mei, Shenghua Liu, Yiwei Wang, Baolong Bi, Xueqi Cheng (2024). SLANG: New Concept Comprehension of Large Language Models. Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024, Miami, FL, USA, November 12-16, 2024.

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

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

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

Baolong Bi, Shenghua Liu, Yiwei Wang, Lingrui Mei, Xueqi Cheng (2024). LPNL: Scalable Link Prediction with Large Language Models. Findings of the Association for Computational Linguistics, ACL 2024, Bangkok, Thailand and virtual meeting, August 11-16, 2024.

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

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

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

Houquan Zhou, Shenghua Liu, Huawei Shen, Xueqi Cheng (2024). Graph Summarization for Preserving Spectral Characteristics. Proceedings of the 2024 SIAM International Conference on Data Mining, SDM 2024, Houston, TX, USA, April 18-20, 2024.

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

Baolong Bi, Shaohan Huang, Yiwei Wang, Tianchi Yang, Zihan Zhang, Haizhen Huang, Lingrui Mei, Junfeng Fang, Zehao Li, Furu Wei, Weiwei Deng, Feng Sun, Qi Zhang, Shenghua Liu (2024). Context-DPO: Aligning Language Models for Context-Faithfulness. arXiv.

Baolong Bi, Shenghua Liu, Yiwei Wang, Lingrui Mei, Hongcheng Gao, Yilong Xu, Xueqi Cheng (2024). Adaptive Token Biaser: Knowledge Editing via Biasing Key Entities. Findings of the Association for Computational Linguistics: EMNLP 2024, Miami, Florida, USA, November 12-16, 2024.

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

Lingrui Mei, Shenghua Liu, Yiwei Wang, Baolong Bi, Jiayi Mao, Xueqi Cheng (2024). \"Not Aligned\" is Not \"Malicious\": Being Careful about Hallucinations of Large Language Models' Jailbreak. arXiv.

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

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

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

Houquan Zhou, Shenghua Liu, Danai Koutra, Huawei Shen, Xueqi Cheng (2023). A Provable Framework of Learning Graph Embeddings via Summarization. Thirty-Seventh AAAI Conference on Artificial Intelligence, AAAI 2023, Thirty-Fifth Conference on Innovative Applications of Artificial Intelligence, IAAI 2023, Thirteenth Symposium on Educational Advances in Artificial Intelligence, EAAI 2023, Washington, DC, USA, February 7-14, 2023.

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

Xiaobing Sun, Wenjie Feng, Shenghua Liu, Yuyang Xie, Siddharth Bhatia, Bryan Hooi, Wenhan Wang, Xueqi Cheng (2022). MonLAD: Money Laundering Agents Detection in Transaction Streams. WSDM ‘22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21 - 25, 2022.

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

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

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

Houquan Zhou, Shenghua Liu, Kyuhan Lee, Kijung Shin, Huawei Shen, Xueqi Cheng (2021). DPGS: Degree-Preserving Graph Summarization. Proceedings of the 2021 SIAM International Conference on Data Mining, SDM 2021, Virtual Event, April 29 - May 1, 2021.

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Xiaobing Sun, Jiabao Zhang, Qiming Zhao, Shenghua Liu, Jinglei Chen, Ruoyu Zhuang, Huawei Shen, Xueqi Cheng (2021). CubeFlow: Money Laundering Detection with Coupled Tensors. Advances in Knowledge Discovery and Data Mining - 25th Pacific-Asia Conference, PAKDD 2021, Virtual Event, May 11-14, 2021, Proceedings, Part I.

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

Xueqi Cheng, Shenghua Liu, Xiaoqian Sun, Zidong Wang, Houquan Zhou, Yu Shao, Huawei Shen (2021). Combating Emerging Financial Risks in the Big Data Era: A Perspective Review. Fundamental Research.

Jiabao Zhang, Shenghua Liu, Wenting Hou, Siddharth Bhatia, Huawei Shen, Wenjian Yu, Xueqi Cheng (2021). AugSplicing: Synchronized Behavior Detection in Streaming Tensors. Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021, Thirty-Third Conference on Innovative Applications of Artificial Intelligence, IAAI 2021, The Eleventh Symposium on Educational Advances in Artificial Intelligence, EAAI 2021, Virtual Event, February 2-9, 2021.

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

Wenjie Feng, Shenghua Liu, Danai Koutra, Huawei Shen, Xueqi Cheng (2020). SpecGreedy: Unified Dense Subgraph Detection. Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2020, Ghent, Belgium, September 14-18, 2020, Proceedings, Part I.

Yiwei Wang, Shenghua Liu, Minji Yoon, Hemank Lamba, Wei Wang, Christos Faloutsos, Bryan Hooi (2020). Provably Robust Node Classification via Low-Pass Message Passing. 20th IEEE International Conference on Data Mining, ICDM 2020, Sorrento, Italy, November 17-20, 2020.

Xiangfeng Li, Shenghua Liu, Zifeng Li, Xiaotian Han, Chuan Shi, Bryan Hooi, He Huang, Xueqi Cheng (2020). FlowScope: Spotting Money Laundering Based on Graphs. The Thirty-Fourth AAAI Conference on Artificial Intelligence, AAAI 2020, The Thirty-Second Innovative Applications of Artificial Intelligence Conference, IAAI 2020, The Tenth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2020, New York, NY, USA, February 7-12, 2020.

Xiangyun Ding, Wenjian Yu, Yuyang Xie, Shenghua Liu (2020). Efficient Model-Based Collaborative Filtering with Fast Adaptive PCA. 32nd IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2020, Baltimore, MD, USA, November 9-11, 2020.

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

Jiabao Zhang, Shenghua Liu, Wenting Hou, Siddharth Bhatia, Huawei Shen, Wenjian Yu, Xueqi Cheng (2020). AugSplicing: Synchronized Behavior Detection in Streaming Tensors. arXiv.

Bryan Hooi, Kijung Shin, Shenghua Liu, Christos Faloutsos (2019). SMF: Drift-Aware Matrix Factorization with Seasonal Patterns. Proceedings of the 2019 SIAM International Conference on Data Mining, SDM 2019, Calgary, Alberta, Canada, May 2-4, 2019.

Jiabao Zhang, Shenghua Liu, Wenjian Yu, Wenjie Feng, Xueqi Cheng (2019). EigenPulse: Detecting Surges in Large Streaming Graphs with Row Augmentation. Advances in Knowledge Discovery and Data Mining - 23rd Pacific-Asia Conference, PAKDD 2019, Macau, China, April 14-17, 2019, Proceedings, Part II.

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

Wenjie Feng, Shenghua Liu, Xueqi Cheng (2019). CatchCore: Catching Hierarchical Dense Subtensor. Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2019, Würzburg, Germany, September 16-20, 2019, Proceedings, Part I.

Wenjie Feng, Shenghua Liu, Christos Faloutsos, Bryan Hooi, Huawei Shen, Xueqi Cheng (2019). Beyond Outliers and on to Micro-clusters: Vision-Guided Anomaly Detection. Advances in Knowledge Discovery and Data Mining - 23rd Pacific-Asia Conference, PAKDD 2019, Macau, China, April 14-17, 2019, Proceedings, Part I.

Bin Zhou, Shenghua Liu, Bryan Hooi, Xueqi Cheng, Jing Ye (2019). BeatGAN: Anomalous Rhythm Detection using Adversarially Generated Time Series. Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, IJCAI 2019, Macao, China, August 10-16, 2019.

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

Pudi Chen, Shenghua Liu, Chuan Shi, Bryan Hooi, Bai Wang, Xueqi Cheng (2018). NeuCast: Seasonal Neural Forecast of Power Grid Time Series. Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, IJCAI 2018, July 13-19, 2018, Stockholm, Sweden.

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

Jian Liu, Chuan Shi, Binbin Hu, Shenghua Liu, Philip S. Yu (2017). Personalized Ranking Recommendation via Integrating Multiple Feedbacks. Advances in Knowledge Discovery and Data Mining - 21st Pacific-Asia Conference, PAKDD 2017, Jeju, South Korea, May 23-26, 2017, Proceedings, Part II.

Yongqing Wang, Shenghua Liu, Huawei Shen, Jinhua Gao, Xueqi Cheng (2017). Marked Temporal Dynamics Modeling Based on Recurrent Neural Network. Advances in Knowledge Discovery and Data Mining - 21st Pacific-Asia Conference, PAKDD 2017, Jeju, South Korea, May 23-26, 2017, Proceedings, Part I.

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

Shenghua Liu, Houdong Zheng, Huawei Shen, Xueqi Cheng, Xiangwen Liao (2017). Learning Concise Representations of Users' Influences through Online Behaviors. Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, IJCAI 2017, Melbourne, Australia, August 19-25, 2017.

Shenghua Liu, Bryan Hooi, Christos Faloutsos (2017). HoloScope: Topology-and-Spike Aware Fraud Detection. Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, CIKM 2017, Singapore, November 06 - 10, 2017.

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

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

Yongqing Wang, Huawei Shen, Shenghua Liu, Jinhua Gao, Xueqi Cheng (2017). Cascade Dynamics Modeling with Attention-based Recurrent Neural Network. Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, IJCAI 2017, Melbourne, Australia, August 19-25, 2017.

Bryan Hooi, Shenghua Liu, Asim Smailagic, Christos Faloutsos (2017). BeatLex: Summarizing and Forecasting Time Series with Patterns. Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18-22, 2017, Proceedings, Part II.

Tong Man, Huawei Shen, Shenghua Liu, Xiaolong Jin, Xueqi Cheng (2016). Predict Anchor Links across Social Networks via an Embedding Approach. Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI 2016, New York, NY, USA, 9-15 July 2016.

Jinhua Gao, Huawei Shen, Shenghua Liu, Xueqi Cheng (2016). Modeling and Predicting Retweeting Dynamics via a Mixture Process. Proceedings of the 25th International Conference on World Wide Web, WWW 2016, Montreal, Canada, April 11-15, 2016, Companion Volume.

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

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

Yongqing Wang, Huawei Shen, Shenghua Liu, Xueqi Cheng (2015). Learning User-Specific Latent Influence and Susceptibility from Information Cascades. Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, January 25-30, 2015, Austin, Texas, USA.

Fangtao Li, Sheng Wang, Shenghua Liu, Ming Zhang (2014). SUIT: A Supervised User-Item Based Topic Model for Sentiment Analysis. Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, July 27 -31, 2014, Québec City, Québec, Canada.

Zhankun Huang, Shenghua Liu, Pan Du, Xueqi Cheng (2014). Ranking Tweets with Local and Global Consistency Using Rich Features. Advances in Knowledge Discovery and Data Mining - 18th Pacific-Asia Conference, PAKDD 2014, Tainan, Taiwan, May 13-16, 2014. Proceedings, Part I.

Shenghua Liu, Xueqi Cheng, Fangtao Li (2014). Ranking Tweets by Labeled and Collaboratively Selected Pairs with Transitive Closure. Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, July 27 -31, 2014, Québec City, Québec, Canada.

Xueqi Cheng, Jiafeng Guo, Shenghua Liu, Yanfeng Wang, Xiaohui Yan (2013). Learning Topics in Short Texts by Non-negative Matrix Factorization on Term Correlation Matrix. Proceedings of the 13th SIAM International Conference on Data Mining, May 2-4, 2013. Austin, Texas, USA.

Shenghua Liu, Wenjun Zhu, Ning Xu, Fangtao Li, Xueqi Cheng, Yue Liu, Yuanzhuo Wang (2013). Co-training and visualizing sentiment evolvement for tweet events. 22nd International World Wide Web Conference, WWW ‘13, Rio de Janeiro, Brazil, May 13-17, 2013, Companion Volume.

Shenghua Liu, Fuxin Li, Fangtao Li, Xueqi Cheng, Huawei Shen (2013). Adaptive co-training SVM for sentiment classification on tweets. 22nd ACM International Conference on Information and Knowledge Management, CIKM'13, San Francisco, CA, USA, October 27 - November 1, 2013.

Xiaohui Yan, Jiafeng Guo, Shenghua Liu, Xueqi Cheng, Yanfeng Wang (2012). Clustering short text using Ncut-weighted non-negative matrix factorization. 21st ACM International Conference on Information and Knowledge Management, CIKM'12, Maui, HI, USA, October 29 - November 02, 2012.

Shenghua Liu, Yuchun Ma, Xianlong Hong, Yu Wang (2010). Simultaneous slack budgeting and retiming for synchronous circuits optimization. Proceedings of the 15th Asia South Pacific Design Automation Conference, ASP-DAC 2010, Taipei, Taiwan, January 18-21, 2010.

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

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

Shenghua Liu, Guoqiang Chen, Tom Tong Jing, Lei He, Robi Dutta, Xianlong Hong (2009). Diffusion-driven congestion reduction for substrate topological routing. Proceedings of the 2009 International Symposium on Physical Design, ISPD 2009, San Diego, California, USA, March 29 - April 1, 2009.

Shenghua Liu, Guoqiang Chen, Tom Tong Jing, Lei He, Tianpei Zhang, Robi Dutta, Xianlong Hong (2008). Topological routing to maximize routability for package substrate. Proceedings of the 45th Design Automation Conference, DAC 2008, Anaheim, CA, USA, June 8-13, 2008.

Shenghua Liu, Xianlong Hong, Tong Jing, Jingyu Xu (2006). FREe: a fast routability estimator. 2006 International Conference on Communications, Circuits and Systems.