| 2026 | AAAI | CP-Router: An Uncertainty-Aware Router Between LLM and LRM. | Jiayuan Su, Fulin Lin, Zhaopeng Feng, Han Zheng, Teng Wang, Zhenyu Xiao, Xinlong Zhao, Zuozhu Liu, Lu Cheng, Hongwei Wang |
| 2026 | ACL | QuCo-RAG: Quantifying Uncertainty from the Pre-training Corpus for Dynamic Retrieval-Augmented Generation. | Dehai Min, Kailin Zhang, Tongtong Wu, Lu Cheng |
| 2026 | ACL | When and What to Ask: AskBench and Rubric-Guided RLVR for LLM Clarification. | Jiale Zhao, Ke Fang, Lu Cheng |
| 2026 | ACL | Robust Uncertainty Quantification for Self-Evolving Large Language Models via Continual Domain Pretraining. | Xiaofan Zhou, Lu Cheng |
| 2026 | PAKDD | Evaluating Social Bias in RAG Systems: When External Context Helps and Reasoning Hurts. | Shweta Parihar, Lu Cheng |
| 2026 | PAKDD | SELAUR: Self Evolving LLM Agent via Uncertainty-Aware Rewards. | Dengjia Zhang, Xiaoou Liu, Lu Cheng, Yaqing Wang, Kenton Murray, Hua Wei |
| 2026 | PAKDD | Smart Trial: Evaluating LLMs for Recruiting Clinical Trial Participants on Social Media. | Xiaofan Zhou, Zisu Wang, Janice L. Krieger, Mohan Zalake, Lu Cheng |
| 2026 | WSDM | Causal Discovery for Biology: From Molecular to Disease Networks. | Lu Cheng |
| 2025 | AAAI | Towards Trustworthy Knowledge Graph Reasoning: An Uncertainty Aware Perspective. | Bo Ni, Yu Wang, Lu Cheng, Erik Blasch, Tyler Derr |
| 2025 | CIKM | Socially Responsible and Trustworthy Generative Foundation Models: Principles, Challenges, and Practices. | Yue Huang, Canyu Chen, Lu Cheng, Bhavya Kailkhura, Nitesh V. Chawla, Xiangliang Zhang |
| 2025 | COLING | Unveiling Performance Challenges of Large Language Models in Low-Resource Healthcare: A Demographic Fairness Perspective. | Yue Zhou, Barbara Di Eugenio, Lu Cheng |
| 2025 | EMNLP | From Generation to Judgment: Opportunities and Challenges of LLM-as-a-judge. | Dawei Li, Bohan Jiang, Liangjie Huang, Alimohammad Beigi, Chengshuai Zhao, Zhen Tan, Amrita Bhattacharjee, Yuxuan Jiang, Canyu Chen, Tianhao Wu, Kai Shu, Lu Cheng, Huan Liu |
| 2025 | EMNLP | Large Vision-Language Model Alignment and Misalignment: A Survey Through the Lens of Explainability. | Dong Shu, Haiyan Zhao, Jingyu Hu, Weiru Liu, Ali Payani, Lu Cheng, Mengnan Du |
| 2025 | IJCAI | Interpreting Pretrained Language Models via Concept Bottlenecks (Extended Abstract). | Zhen Tan, Lu Cheng, Song Wang, Bo Yuan, Jundong Li, Huan Liu |
| 2025 | IJCNLP | Moral Self-correction is Not An Innate Capability in Language Models. | Guangliang Liu, Zimo Qi, Xitong Zhang, Lu Cheng, Kristen Marie Johnson |
| 2025 | KDD | SciSoc LLM Workshop: Large Language Models for Scientific and Societal Advances. | Wei Jin, Lu Cheng, Wenpeng Yin, Xianfeng Tang, Qingsong Wen, Danai Koutra, B. Aditya Prakash, Yan Liu |
| 2025 | NAACL | Threshold Filtering Packing for Supervised Fine-Tuning: Training Related Samples within Packs. | Jiancheng Dong, Lei Jiang, Wei Jin, Lu Cheng |
| 2025 | VTC | Air-Ground Model Collaboration for Low-Altitude Intelligent Networks with Heterogeneous Computational Resources. | Lu Cheng, Shuhang Zhang, Hongliang Zhang, Qingyu Liu, Mohammed Karmoose, Kangjun Liu, Yaowei Wang |
| 2025 | VTC | Fine-Grained Radio Map Construction from Ultra-Sparse Sampling: An Edge-Cloud Model Collaboration Paradigm. | Shuai Shao, Lu Cheng, Ke Chen, Shuhang Zhang, Lingyang Song |
| 2024 | AAAI | Demystifying Algorithmic Fairness in an Uncertain World. | Lu Cheng |
| 2024 | ACL | JORA: JAX Tensor-Parallel LoRA Library for Retrieval Augmented Fine-Tuning. | Anique Tahir, Lu Cheng, Huan Liu |
| 2024 | DSAA | Media Bias Matters: Understanding the Impact of Politically Biased News on Vaccine Attitudes in Social Media. | Bohan Jiang, Lu Cheng, Zhen Tan, Ruocheng Guo, Huan Liu |
| 2024 | EMNLP | LLMs Assist NLP Researchers: Critique Paper (Meta-)Reviewing. | Jiangshu Du, Yibo Wang, Wenting Zhao, Zhongfen Deng, Shuaiqi Liu, Renze Lou, Henry Peng Zou, Pranav Narayanan Venkit, Nan Zhang, Mukund Srinath, Haoran Zhang, Vipul Gupta, Yinghui Li, Tao Li, Fei Wang, Qin Liu, Tianlin Liu, Pengzhi Gao, Congying Xia, Chen Xing, Cheng Jiayang, Zhaowei Wang, Ying Su, Raj Sanjay Shah, Ruohao Guo, Jing Gu, Haoran Li, Kangda Wei, Zihao Wang, Lu Cheng, Surangika Ranathunga, Meng Fang, Jie Fu, Fei Liu, Ruihong Huang, Eduardo Blanco, Yixin Cao, Rui Zhang, Philip S. Yu, Wenpeng Yin |
| 2024 | EMNLP | API Is Enough: Conformal Prediction for Large Language Models Without Logit-Access. | Jiayuan Su, Jing Luo, Hongwei Wang, Lu Cheng |
| 2024 | EMNLP | Large Language Models for Data Annotation and Synthesis: A Survey. | Zhen Tan, Dawei Li, Song Wang, Alimohammad Beigi, Bohan Jiang, Amrita Bhattacharjee, Mansooreh Karami, Jundong Li, Lu Cheng, Huan Liu |
| 2024 | EMNLP | ConU: Conformal Uncertainty in Large Language Models with Correctness Coverage Guarantees. | Zhiyuan Wang, Jinhao Duan, Lu Cheng, Yue Zhang, Qingni Wang, Xiaoshuang Shi, Kaidi Xu, Heng Tao Shen, Xiaofeng Zhu |
| 2024 | KDD | Conformalized Link Prediction on Graph Neural Networks. | Tianyi Zhao, Jian Kang, Lu Cheng |
| 2024 | KDD | A Survey on Safe Multi-Modal Learning Systems. | Tianyi Zhao, Liangliang Zhang, Yao Ma, Lu Cheng |
| 2024 | PAKDD | Interpreting Pretrained Language Models via Concept Bottlenecks. | Zhen Tan, Lu Cheng, Song Wang, Bo Yuan, Jundong Li, Huan Liu |
| 2024 | WWW | AI Driven Online Advertising: Market Design, Generative AI, and Ethics. | Fengxiang He, Mengnan Du, Aris Filos-Ratsikas, Lu Cheng, Qingquan Song, Min Lin, John Vines |
| 2023 | CIKM | Fairness through Aleatoric Uncertainty. | Anique Tahir, Lu Cheng, Huan Liu |
| 2023 | CIKM | Unveiling the Role of Message Passing in Dual-Privacy Preservation on GNNs. | Tianyi Zhao, Hui Hu, Lu Cheng |
| 2023 | ECAI | Fair Few-Shot Learning with Auxiliary Sets. | Song Wang, Jing Ma, Lu Cheng, Jundong Li |
| 2023 | IJCAI | A Survey on Intersectional Fairness in Machine Learning: Notions, Mitigation, and Challenges. | Usman Gohar, Lu Cheng |
| 2022 | CIKM | Joint Clothes Detection and Attribution Prediction via Anchor-free Framework with Decoupled Representation Transformer. | Fankai Zeng, Mingbo Zhao, Zhao Zhang, Shanchuan Gao, Lu Cheng |
| 2022 | CogSci | Joint Content-Context Analysis of Scientific Publications: Identifying Opportunities for Collaboration in Cognitive Science. | Lu Cheng, Harlin Lee, Girish Ganesan, William L. He, Daniel Silverston, Jacob G. Foster |
| 2022 | COLING | Debiasing Word Embeddings with Nonlinear Geometry. | Lu Cheng, Nayoung Kim, Huan Liu |
| 2022 | ICWSM | Effects of Multi-Aspect Online Reviews with Unobserved Confounders: Estimation and Implication. | Lu Cheng, Ruocheng Guo, Kasim Seluk Candan, Huan Liu |
| 2022 | WWW | Learning Privacy-Preserving Graph Convolutional Network with Partially Observed Sensitive Attributes. | Hui Hu, Lu Cheng, Jayden Parker Vap, Mike Borowczak |
| 2022 | SIGIR | Bias Mitigation for Toxicity Detection via Sequential Decisions. | Lu Cheng, Ahmadreza Mosallanezhad, Yasin N. Silva, Deborah L. Hall, Huan Liu |
| 2022 | WSDM | Estimating Causal Effects of Multi-Aspect Online Reviews with Multi-Modal Proxies. | Lu Cheng, Ruocheng Guo, Huan Liu |
| 2022 | WSDM | Causal Mediation Analysis with Hidden Confounders. | Lu Cheng, Ruocheng Guo, Huan Liu |
| 2022 | SISAP | Causal Disentanglement with Network Information for Debiased Recommendations. | Paras Sheth, Ruocheng Guo, Kaize Ding, Lu Cheng, K. Seluk Candan, Huan Liu |
| 2021 | ACL | Mitigating Bias in Session-based Cyberbullying Detection: A Non-Compromising Approach. | Lu Cheng, Ahmadreza Mosallanezhad, Yasin N. Silva, Deborah L. Hall, Huan Liu |
| 2021 | IJCAI | Causal Learning for Socially Responsible AI. | Lu Cheng, Ahmadreza Mosallanezhad, Paras Sheth, Huan Liu |
| 2021 | KDD | Causal Understanding of Fake News Dissemination on Social Media. | Lu Cheng, Ruocheng Guo, Kai Shu, Huan Liu |
| 2021 | WWW | Improving Cyberbullying Detection with User Interaction. | Suyu Ge, Lu Cheng, Huan Liu |
| 2021 | WSDM | Long-Term Effect Estimation with Surrogate Representation. | Lu Cheng, Ruocheng Guo, Huan Liu |
| 2020 | AAAI | Tracking Disaster Footprints with Social Streaming Data. | Lu Cheng, Jundong Li, K. Seluk Candan, Huan Liu |
| 2020 | CIKM | Unsupervised Cyberbullying Detection via Time-Informed Gaussian Mixture Model. | Lu Cheng, Kai Shu, Siqi Wu, Yasin N. Silva, Deborah L. Hall, Huan Liu |
| 2020 | ICCE | Changes in the effect of concept map-based autonomous learning under different levels of self-regulation. | Lu Cheng, Fan Chen, Jiayu Niu, Xueying Xu, Ning Ma |
| 2020 | SDM | Representation Learning for Imbalanced Cross-Domain Classification. | Lu Cheng, Ruocheng Guo, K. Seluk Candan, Huan Liu |
| 2019 | IJCAI | PI-Bully: Personalized Cyberbullying Detection with Peer Influence. | Lu Cheng, Jundong Li, Yasin N. Silva, Deborah L. Hall, Huan Liu |
| 2019 | WWW | Robust Cyberbullying Detection with Causal Interpretation. | Lu Cheng, Ruocheng Guo, Huan Liu |
| 2019 | WSDM | XBully: Cyberbullying Detection within a Multi-Modal Context. | Lu Cheng, Jundong Li, Yasin N. Silva, Deborah L. Hall, Huan Liu |
| 2019 | SDM | Hierarchical Attention Networks for Cyberbullying Detection on the Instagram Social Network. | Lu Cheng, Ruocheng Guo, Yasin N. Silva, Deborah L. Hall, Huan Liu |
| 2018 | ICCE | A Comparative Study on Achievement Degree of Teaching Objectives based on an Interactive AR Physical-Simulation Experimental Procedure. | Xiaojie Niu, Xueying Xu, Lu Cheng, Su Cai |
| 2017 | CISIS | Distinguishing Property for Full Round KECCAK-f Permutation. | Maolin Li, Lu Cheng |
| 2011 | CNSM | Mitigating the negative impact of preemption on heterogeneous MapReduce workloads. | Lu Cheng, Qi Zhang, Raouf Boutaba |
| 2010 | CNSM | An efficient active probing approach based on the combination of online and offline strategies. | Likun Yu, Lu Cheng, Yan Qiao, Yiguo Yuan, Xingyu Chen |
| 2010 | GLOBECOM | A Methodology Used to Optimize Probe Selection for Fault Localization. | Yan Qiao, Xuesong Qiu, Lu Cheng, Luoming Meng |
| 2010 | INFOCOM | Efficient Active Probing for Fault Diagnosis in Large Scale and Noisy Networks. | Lu Cheng, Xuesong Qiu, Luoming Meng, Yan Qiao, Raouf Boutaba |
| 2009 | APNOMS | Fault Diagnosis for High-Level Applications Based on Dynamic Bayesian Network. | Zhiqing Li, Lu Cheng, Xuesong Qiu, Li Wu |
| 2009 | APNOMS | An Algorithm for the Measure Station Selection and Measure Assignment in the Active IP Network Measurement. | Yongguo Zeng, Lu Cheng, Ting Huang, Zhiqing Li |
| 2009 | ICNC | Fault Diagnosis for Large-Scale IP Networks Based on Dynamic Bayesian Model. | Zhiqing Li, Lu Cheng, Xuesong Qiu, Yongguo Zeng |
| 2009 | IM | Probabilistic fault diagnosis for IT services in noisy and dynamic environments. | Lu Cheng, Xuesong Qiu, Luoming Meng, Yan Qiao, Zhiqing Li |
| 2008 | APNOMS | Active Diagnosis of High-Level Faults in Distributed Internet Services. | Huihu Long, Lu Cheng, Yongguo Zeng, Li Wu |