A Practical Data Repository for Causal Learning with Big Data. - Lu Cheng 001; Ruocheng Guo; Raha Moraffah; K. Selçuk Candan; Adrienne Raglin; Huan Liu 001 (Bench, 2019)

PI-Bully: Personalized Cyberbullying Detection with Peer Influence. - Lu Cheng 001; Jundong Li; Yasin N. Silva; Deborah L. Hall; Huan Liu 001 (IJCAI, 2019)

Hierarchical Attention Networks for Cyberbullying Detection on the Instagram Social Network. - Lu Cheng 001; Ruocheng Guo; Yasin N. Silva; Deborah L. Hall; Huan Liu 001 (SDM, 2019)

XBully: Cyberbullying Detection within a Multi-Modal Context. - Lu Cheng 001; Jundong Li; Yasin N. Silva; Deborah L. Hall; Huan Liu 001 (WSDM, 2019)

Robust Cyberbullying Detection with Causal Interpretation. - Lu Cheng 001; Ruocheng Guo; Huan Liu 001 (WWW (Companion Volume), 2019)

Tracking Disaster Footprints with Social Streaming Data. - Lu Cheng 001; Jundong Li; K. Selçuk Candan; Huan Liu 001 (AAAI, 2020)

Unsupervised Cyberbullying Detection via Time-Informed Gaussian Mixture Model. - Lu Cheng 001; Kai Shu; Siqi Wu; Yasin N. Silva; Deborah L. Hall; Huan Liu 001 (CIKM, 2020)

Representation Learning for Imbalanced Cross-Domain Classification. - Lu Cheng 001; Ruocheng Guo; K. Selçuk Candan; Huan Liu 001 (SDM, 2020)

Towards Causal Understanding of Fake News Dissemination. - Lu Cheng 001; Ruocheng Guo; Kai Shu; Huan Liu 001 (CoRR, 2020)

Improving Cyberbully Detection with User Interaction. - Suyu Ge; Lu Cheng 001; Huan Liu 001 (CoRR, 2020)

Mitigating Bias in Session-based Cyberbullying Detection: A Non-Compromising Approach. - Lu Cheng 001; Ahmadreza Mosallanezhad; Yasin N. Silva; Deborah L. Hall; Huan Liu 001 (ACL/IJCNLP (1), 2021)

Causal Learning for Socially Responsible AI. - Lu Cheng 001; Ahmadreza Mosallanezhad; Paras Sheth; Huan Liu 001 (IJCAI, 2021)

Causal Understanding of Fake News Dissemination on Social Media. - Lu Cheng 001; Ruocheng Guo; Kai Shu; Huan Liu 001 (KDD, 2021)

Long-Term Effect Estimation with Surrogate Representation. - Lu Cheng 001; Ruocheng Guo; Huan Liu 001 (WSDM, 2021)

Improving Cyberbullying Detection with User Interaction. - Suyu Ge; Lu Cheng 001; Huan Liu 001 (WWW, 2021)

Automated Meta-Analysis: A Causal Learning Perspective. - Lu Cheng 001; Dmitriy A. Katz-Rogozhnikov; Kush R. Varshney; Ioana Baldini (CoRR, 2021)

Mechanisms and Attributes of Echo Chambers in Social Media. - Bohan Jiang; Mansooreh Karami; Lu Cheng 001; Tyler Black; Huan Liu 001 (CoRR, 2021)

A Survey on Echo Chambers on Social Media: Description, Detection and Mitigation. - Faisal Alatawi; Lu Cheng 001; Anique Tahir; Mansooreh Karami; Bohan Jiang; Tyler Black; Huan Liu 001 (CoRR, 2021)

A Survey of Learning Causality with Data: Problems and Methods. - Ruocheng Guo; Lu Cheng 001; Jundong Li; P. Richard Hahn; Huan Liu 001 (ACM Comput. Surv., 2021)

Session-Based Cyberbullying Detection: Problems and Challenges. - Lu Cheng 001; Yasin N. Silva; Deborah L. Hall; Huan Liu 001 (IEEE Internet Comput., 2021)

Socially Responsible AI Algorithms: Issues, Purposes, and Challenges. - Lu Cheng 001; Kush R. Varshney; Huan Liu 001 (J. Artif. Intell. Res., 2021)

Modeling Temporal Patterns of Cyberbullying Detection with Hierarchical Attention Networks. - Lu Cheng 001; Ruocheng Guo; Yasin N. Silva; Deborah L. Hall; Huan Liu 001 (Trans. Data Sci., 2021)

Nothing Stands Alone: Relational Fake News Detection with Hypergraph Neural Networks. - Ujun Jeong; Kaize Ding; Lu Cheng 001; Ruocheng Guo; Kai Shu; Huan Liu 001 (IEEE Big Data, 2022)

Distributional Shift Adaptation using Domain-Specific Features. - Anique Tahir; Lu Cheng 001; Ruocheng Guo; Huan Liu 001 (IEEE Big Data, 2022)

Debiasing Word Embeddings with Nonlinear Geometry. - Lu Cheng 001; Nayoung Kim; Huan Liu 001 (COLING, 2022)

Effects of Multi-Aspect Online Reviews with Unobserved Confounders: Estimation and Implication. - Lu Cheng 001; Ruocheng Guo; Kasim Selçuk Candan; Huan Liu 001 (ICWSM, 2022)

Classifying COVID-19 Related Meta Ads Using Discourse Representation Through a Hypergraph. - Ujun Jeong; Zeyad Alghamdi; Kaize Ding; Lu Cheng 001; Baoxin Li; Huan Liu 001 (SBP-BRiMS, 2022)

Bias Mitigation for Toxicity Detection via Sequential Decisions. - Lu Cheng 001; Ahmadreza Mosallanezhad; Yasin N. Silva; Deborah L. Hall; Huan Liu 001 (SIGIR, 2022)

Causal Disentanglement with Network Information for Debiased Recommendations. - Paras Sheth; Ruocheng Guo; Kaize Ding; Lu Cheng 001; K. Selçuk Candan; Huan Liu 001 (SISAP, 2022)

Estimating Causal Effects of Multi-Aspect Online Reviews with Multi-Modal Proxies. - Lu Cheng 001; Ruocheng Guo; Huan Liu 001 (WSDM, 2022)

Causal Mediation Analysis with Hidden Confounders. - Lu Cheng 001; Ruocheng Guo; Huan Liu 001 (WSDM, 2022)

Learning Privacy-Preserving Graph Convolutional Network with Partially Observed Sensitive Attributes. - Hui Hu; Lu Cheng 001; Jayden Parker Vap; Mike Borowczak (WWW, 2022)

Causal Disentanglement with Network Information for Debiased Recommendations. - Paras Sheth; Ruocheng Guo; Lu Cheng 001; Huan Liu 001; K. Selçuk Candan (CoRR, 2022)

Toward Understanding Bias Correlations for Mitigation in NLP. - Lu Cheng 001; Suyu Ge; Huan Liu 001 (CoRR, 2022)

Bridging the Gap: Commonality and Differences between Online and Offline COVID-19 Data. - Nayoung Kim; Ahmadreza Mosallanezhad; Lu Cheng 001; Baoxin Li; Huan Li (CoRR, 2022)

Improving Vaccine Stance Detection by Combining Online and Offline Data. - Anique Tahir; Lu Cheng 001; Paras Sheth; Huan Liu 001 (CoRR, 2022)

Learning Shared Mobility-Aware Knowledge for Multiple Urban Travel Demands. - Qianru Wang; Bin Guo 001; Yi Ouyang 003; Lu Cheng 001; Liang Wang 017; Zhiwen Yu 001; Huan Liu 001 (IEEE Internet Things J., 2022)

Evaluation Methods and Measures for Causal Learning Algorithms. - Lu Cheng 001; Ruocheng Guo; Raha Moraffah; Paras Sheth; K. Selçuk Candan; Huan Liu 001 (IEEE Trans. Artif. Intell., 2022)

Socially Responsible AI - Theories and Practices - Lu Cheng 001; Huan Liu 001 (Socially Responsible AI, 2023)

Intersectionality and Testimonial Injustice in Medical Records. - Kenya S. Andrews; Bhuvni Shah; Lu Cheng 001 (ClinicalNLP@ACL, 2023)

Fairness through Aleatoric Uncertainty. - Anique Tahir; Lu Cheng 001; Huan Liu 001 (CIKM, 2023)

Unveiling the Role of Message Passing in Dual-Privacy Preservation on GNNs. - Tianyi Zhao; Hui Hu; Lu Cheng 001 (CIKM, 2023)

Fair Few-Shot Learning with Auxiliary Sets. - Song Wang 013; Jing Ma 002; Lu Cheng 001; Jundong Li (ECAI, 2023)

A Survey on Intersectional Fairness in Machine Learning: Notions, Mitigation, and Challenges. - Usman Gohar; Lu Cheng 001 (IJCAI, 2023)

Equal Opportunity of Coverage in Fair Regression. - Fangxin Wang 003; Lu Cheng 001; Ruocheng Guo; Kay Liu; Philip S. Yu (NeurIPS, 2023)

Intersectionality and Testimonial Injustice in Medical Records. - Kenya S. Andrews; Bhuvani Shah; Lu Cheng 001 (CoRR, 2023)

STANCE-C3: Domain-adaptive Cross-target Stance Detection via Contrastive Learning and Counterfactual Generation. - Nayoung Kim; David Mosallanezhad; Lu Cheng 001; Michelle V. Mancenido; Huan Liu 001 (CoRR, 2023)

A Theoretical Approach to Characterize the Accuracy-Fairness Trade-off Pareto Frontier. - Hua Tang; Lu Cheng 001; Ninghao Liu; Mengnan Du (CoRR, 2023)

Interpreting Pretrained Language Models via Concept Bottlenecks. - Zhen Tan 001; Lu Cheng 001; Song Wang 013; Yuan Bo; Jundong Li; Huan Liu 001 (CoRR, 2023)

Beyond Detection: Unveiling Fairness Vulnerabilities in Abusive Language Models. - Yueqing Liang; Lu Cheng 001; Ali Payani; Kai Shu (CoRR, 2023)

Causal Disentanglement for Implicit Recommendations with Network Information. - Paras Sheth; Ruocheng Guo; Lu Cheng 001; Huan Liu 001; Kasim Selçuk Candan (ACM Trans. Knowl. Discov. Data, 2023)

CausalSE: Understanding Varied Spatial Effects with Missing Data Toward Adding New Bike-sharing Stations. - Qianru Wang; Bin Guo 001; Lu Cheng 001; Zhiwen Yu 001; Huan Liu 001 (ACM Trans. Knowl. Discov. Data, 2023)

sUrban: Stable Prediction for Unseen Urban Data from Location-based Sensors. - Qianru Wang; Bin Guo 001; Lu Cheng 001; Zhiwen Yu 001 (Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2023)

Robust Stance Detection: Understanding Public Perceptions in Social Media. - Nayoung Kim; David Mosallanezhad; Lu Cheng 001; Michelle V. Mancenido; Huan Liu 001 (ASONAM (2), 2024)

Evaluating LLMs Capabilities Towards Understanding Social Dynamics. - Anique Tahir; Lu Cheng 001; Manuel Sandoval; Yasin N. Silva; Deborah L. Hall; Huan Liu 001 (ASONAM (3), 2024)

Assessing Empathy in Large Language Models with Real-World Physician-Patient Interactions. - Man Luo; Christopher J. Warren; Lu Cheng 001; Haidar M. Abdul-Muhsin; Imon Banerjee (IEEE Big Data, 2024)

Media Bias Matters: Understanding the Impact of Politically Biased News on Vaccine Attitudes in Social Media. - Bohan Jiang; Lu Cheng 001; Zhen Tan 001; Ruocheng Guo; Huan Liu 001 (DSAA, 2024)

LLMs Assist NLP Researchers: Critique Paper (Meta-)Reviewing. - Jiangshu Du; Yibo Wang 001; Wenting Zhao 006; Zhongfen Deng; Shuaiqi Liu 002; Renze Lou; Henry Peng Zou; Pranav Narayanan Venkit; Nan Zhang; Mukund Srinath; Haoran Zhang 004; Vipul Gupta; et al. (EMNLP, 2024)

Large Language Models for Data Annotation and Synthesis: A Survey. - Zhen Tan 001; Dawei Li 008; Song Wang 013; Alimohammad Beigi; Bohan Jiang; Amrita Bhattacharjee; Mansooreh Karami; Jundong Li; Lu Cheng 001; Huan Liu 001 (EMNLP, 2024)

Conformalized Link Prediction on Graph Neural Networks. - Tianyi Zhao; Jian Kang 008; Lu Cheng 001 (KDD, 2024)

A Survey on Safe Multi-Modal Learning Systems. - Tianyi Zhao; Liangliang Zhang; Yao Ma 001; Lu Cheng 001 (KDD, 2024)

Interpreting Pretrained Language Models via Concept Bottlenecks. - Zhen Tan 001; Lu Cheng 001; Song Wang 013; Bo Yuan 017; Jundong Li; Huan Liu 001 (PAKDD (3), 2024)

AI Driven Online Advertising: Market Design, Generative AI, and Ethics. - Fengxiang He; Mengnan Du; Aris Filos-Ratsikas; Lu Cheng 001; Qingquan Song; Min Lin; John Vines (WWW (Companion Volume), 2024)

A Survey on Safe Multi-Modal Learning System. - Tianyi Zhao; Liangliang Zhang; Yao Ma 001; Lu Cheng 001 (CoRR, 2024)

Large Language Models for Data Annotation: A Survey. - Zhen Tan 001; Alimohammad Beigi; Song Wang 013; Ruocheng Guo; Amrita Bhattacharjee; Bohan Jiang; Mansooreh Karami; Jundong Li; Lu Cheng 001; Huan Liu 001 (CoRR, 2024)

Overcoming Pitfalls in Graph Contrastive Learning Evaluation: Toward Comprehensive Benchmarks. - Qian Ma 012; Hongliang Chi; Hengrui Zhang; Kay Liu; Zhiwei Zhang; Lu Cheng 001; Suhang Wang; Philip S. Yu; Yao Ma 001 (CoRR, 2024)

JORA: JAX Tensor-Parallel LoRA Library for Retrieval Augmented Fine-Tuning. - Anique Tahir; Lu Cheng 001; Huan Liu 001 (CoRR, 2024)

Deconstructing The Ethics of Large Language Models from Long-standing Issues to New-emerging Dilemmas. - Chengyuan Deng; Yiqun Duan; Xin Jin; Heng Chang; Yijun Tian 001; Han Liu; Henry Peng Zou; Yiqiao Jin; Yijia Xiao; Yichen Wang; Shenghao Wu; Zongxing Xie; et al. (CoRR, 2024)

LLMs Assist NLP Researchers: Critique Paper (Meta-)Reviewing. - Jiangshu Du; Yibo Wang 001; Wenting Zhao 006; Zhongfen Deng; Shuaiqi Liu 002; Renze Lou; Henry Peng Zou; Pranav Narayanan Venkit; Nan Zhang; Mukund Srinath; Haoran Ranran Zhang; Vipul Gupta; et al. (CoRR, 2024)

Direct-Inverse Prompting: Analyzing LLMs' Discriminative Capacity in Self-Improving Generation. - Jihyun Janice Ahn; Ryo Kamoi; Lu Cheng 001; Rui Zhang 037; Wenpeng Yin 001 (CoRR, 2024)

DemoShapley: Valuation of Demonstrations for In-Context Learning. - Shan Xie; Man Luo; Chadly Daniel Stern; Mengnan Du; Lu Cheng 001 (CoRR, 2024)

From Generation to Judgment: Opportunities and Challenges of LLM-as-a-judge. - Dawei Li 008; Bohan Jiang; Liangjie Huang; Alimohammad Beigi; Chengshuai Zhao; Zhen Tan 001; Amrita Bhattacharjee; Yuxuan Jiang; Canyu Chen; Tianhao Wu; Kai Shu; Lu Cheng 001; et al. (CoRR, 2024)

Long-Term Fairness Inquiries and Pursuits in Machine Learning: A Survey of Notions, Methods, and Challenges. - Usman Gohar; Zeyu Tang 002; Jialu Wang; Kun Zhang 001; Peter Spirtes; Yang Liu 018; Lu Cheng 001 (Trans. Mach. Learn. Res., 2025)

Beyond Accuracy: The Role of Calibration in Self-Improving Large Language Models. - Liangjie Huang; Dawei Li 008; Huan Liu 001; Lu Cheng 001 (CoRR, 2025)

Accelerating Causal Network Discovery of Alzheimer Disease Biomarkers via Scientific Literature-based Retrieval Augmented Generation. - Xiaofan Zhou; Liangjie Huang; Pinyang Cheng; Wenpeng Yin 001; Rui Zhang 037; Wenrui Hao; Lu Cheng 001 (CoRR, 2025)

DBR: Divergence-Based Regularization for Debiasing Natural Language Understanding Models. - Zihao Li; Ruixiang Tang; Lu Cheng 001; Shuaiqiang Wang; Dawei Yin; Mengnan Du (SIGKDD Explor., 2025)