Representation Learning for Treatment Effect Estimation from Observational Data. - Liuyi Yao; Sheng Li 001; Yaliang Li; Mengdi Huai; Jing Gao 004; Aidong Zhang (NeurIPS, 2018)

Online Truth Discovery on Time Series Data. - Liuyi Yao; Lu Su 001; Qi Li 012; Yaliang Li; Fenglong Ma; Jing Gao 004; Aidong Zhang (SDM, 2018)

Finding Similar Medical Questions from Question Answering Websites. - Yaliang Li; Liuyi Yao; Nan Du 001; Jing Gao 004; Qi Li 012; Chuishi Meng; Chenwei Zhang; Wei Fan 001 (CoRR, 2018)

Estimating Brain Effective Connectivity in fMRI data by Non-stationary Dynamic Bayesian Networks. - Jinduo Liu 001; Junzhong Ji; Liuyi Yao; Aidong Zhang (BIBM, 2019)

ACE: Adaptively Similarity-Preserved Representation Learning for Individual Treatment Effect Estimation. - Liuyi Yao; Sheng Li 001; Yaliang Li; Mengdi Huai; Jing Gao 004; Aidong Zhang (ICDM, 2019)

Recurrent Imputation for Multivariate Time Series with Missing Values. - Qiuling Suo; Liuyi Yao; Guangxu Xun; Jianhui Sun; Aidong Zhang (ICHI, 2019)

Deep Metric Learning: The Generalization Analysis and an Adaptive Algorithm. - Mengdi Huai; Hongfei Xue; Chenglin Miao; Liuyi Yao; Lu Su 001; Changyou Chen; Aidong Zhang (IJCAI, 2019)

On the Estimation of Treatment Effect with Text Covariates. - Liuyi Yao; Sheng Li 001; Yaliang Li; Hongfei Xue; Jing Gao 004; Aidong Zhang (IJCAI, 2019)

DTEC: Distance Transformation Based Early Time Series Classification. - Liuyi Yao; Yaliang Li; Yezheng Li; Hengtong Zhang; Mengdi Huai; Jing Gao 004; Aidong Zhang (SDM, 2019)

EC-GAN: Inferring Brain Effective Connectivity via Generative Adversarial Networks. - Jinduo Liu 001; Junzhong Ji; Guangxu Xun; Liuyi Yao; Mengdi Huai; Aidong Zhang (AAAI, 2020)

Causal Inference Meets Machine Learning. - Peng Cui 001; Zheyan Shen; Sheng Li 001; Liuyi Yao; Yaliang Li; Zhixuan Chu; Jing Gao 004 (KDD, 2020)

Malicious Attacks against Deep Reinforcement Learning Interpretations. - Mengdi Huai; Jianhui Sun; Renqin Cai; Liuyi Yao; Aidong Zhang (KDD, 2020)

SCI: Subspace Learning Based Counterfactual Inference for Individual Treatment Effect Estimation. - Liuyi Yao; Yaliang Li; Sheng Li 001; Mengdi Huai; Jing Gao 004; Aidong Zhang (CIKM, 2021)

Deep Staging: An Interpretable Deep Learning Framework for Disease Staging. - Liuyi Yao; Zijun Yao 001; Jianying Hu; Jing Gao 004; Zhaonan Sun (ICHI, 2021)

Debiasing Learning based Cross-domain Recommendation. - Siqing Li; Liuyi Yao; Shanlei Mu; Wayne Xin Zhao; Yaliang Li; Tonglei Guo; Bolin Ding; Ji-Rong Wen (KDD, 2021)

MSLife: Digital Behavioral Phenotyping of Multiple Sclerosis Symptoms in the Wild Using Wearables and Graph-Based Statistical Analysis. - Gabriel Guo; Hanbin Zhang; Liuyi Yao; Huining Li; Chenhan Xu; Zhengxiong Li; Wenyao Xu (Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2021)

A Survey on Causal Inference. - Liuyi Yao; Zhixuan Chu; Sheng Li 001; Yaliang Li; Jing Gao 004; Aidong Zhang (ACM Trans. Knowl. Discov. Data, 2021)

Imbalance-Aware Uplift Modeling for Observational Data. - Xuanying Chen; Zhining Liu 001; Li Yu; Liuyi Yao; Wenpeng Zhang 003; Yi Dong; Lihong Gu; Xiaodong Zeng; Yize Tan; Jinjie Gu (AAAI, 2022)

Towards Automating Model Explanations with Certified Robustness Guarantees. - Mengdi Huai; Jinduo Liu 001; Chenglin Miao; Liuyi Yao; Aidong Zhang (AAAI, 2022)

FederatedScope-GNN: Towards a Unified, Comprehensive and Efficient Package for Federated Graph Learning. - Zhen Wang 036; Weirui Kuang; Yuexiang Xie; Liuyi Yao; Yaliang Li; Bolin Ding; Jingren Zhou 001 (KDD, 2022)

FederatedScope: A Comprehensive and Flexible Federated Learning Platform via Message Passing. - Yuexiang Xie; Zhen Wang 036; Daoyuan Chen; Dawei Gao; Liuyi Yao; Weirui Kuang; Yaliang Li; Bolin Ding; Jingren Zhou 001 (CoRR, 2022)

A Benchmark for Federated Hetero-Task Learning. - Liuyi Yao; Dawei Gao; Zhen Wang 036; Yuexiang Xie; Weirui Kuang; Daoyuan Chen; Haohui Wang; Chenhe Dong; Bolin Ding; Yaliang Li (CoRR, 2022)

On the Robustness of Metric Learning: An Adversarial Perspective. - Mengdi Huai; Tianhang Zheng; Chenglin Miao; Liuyi Yao; Aidong Zhang (ACM Trans. Knowl. Discov. Data, 2022)

Efficient Personalized Federated Learning via Sparse Model-Adaptation. - Daoyuan Chen; Liuyi Yao; Dawei Gao; Bolin Ding; Yaliang Li (ICML, 2023)

Revisiting Personalized Federated Learning: Robustness Against Backdoor Attacks. - Zeyu Qin; Liuyi Yao; Daoyuan Chen; Yaliang Li; Bolin Ding; Minhao Cheng (KDD, 2023)

Path-specific Causal Fair Prediction via Auxiliary Graph Structure Learning. - Liuyi Yao; Yaliang Li; Bolin Ding; Jingren Zhou 001; Jinduo Liu 001; Mengdi Huai; Jing Gao 004 (WWW, 2023)

FederatedScope: A Flexible Federated Learning Platform for Heterogeneity. - Yuexiang Xie; Zhen Wang 036; Dawei Gao; Daoyuan Chen; Liuyi Yao; Weirui Kuang; Yaliang Li; Bolin Ding; Jingren Zhou 001 (Proc. VLDB Endow., 2023)

Concept-Level Model Interpretation From the Causal Aspect. - Liuyi Yao; Yaliang Li; Sheng Li 001; Jinduo Liu 001; Mengdi Huai; Aidong Zhang; Jing Gao 004 (IEEE Trans. Knowl. Data Eng., 2023)

When to Trust LLMs: Aligning Confidence with Response Quality. - Shuchang Tao; Liuyi Yao; Hanxing Ding; Yuexiang Xie; Qi Cao; Fei Sun 001; Jinyang Gao; Huawei Shen; Bolin Ding (ACL (Findings), 2024)

On the Convergence of Zeroth-Order Federated Tuning for Large Language Models. - Zhenqing Ling; Daoyuan Chen; Liuyi Yao; Yaliang Li; Ying Shen 001 (KDD, 2024)

Federated Fine-tuning of Large Language Models under Heterogeneous Tasks and Client Resources. - Jiamu Bai; Daoyuan Chen; Bingchen Qian; Liuyi Yao; Yaliang Li (NeurIPS, 2024)

An Auction-based Marketplace for Model Trading in Federated Learning. - Yue Cui 001; Liuyi Yao; Yaliang Li; Ziqian Chen; Bolin Ding; Xiaofang Zhou 001 (CoRR, 2024)

Federated Fine-tuning of Large Language Models under Heterogeneous Language Tasks and Client Resources. - Jiamu Bai; Daoyuan Chen; Bingchen Qian; Liuyi Yao; Yaliang Li (CoRR, 2024)

AgentScope: A Flexible yet Robust Multi-Agent Platform. - Dawei Gao; Zitao Li; Weirui Kuang; Xuchen Pan; Daoyuan Chen; Zhijian Ma; Bingchen Qian; Liuyi Yao; Lin Zhu; Chen Cheng; Hongzhu Shi; Yaliang Li; et al. (CoRR, 2024)

Double-I Watermark: Protecting Model Copyright for LLM Fine-tuning. - Shen Li; Liuyi Yao; Jinyang Gao; Lan Zhang 002; Yaliang Li (CoRR, 2024)

A Bargaining-based Approach for Feature Trading in Vertical Federated Learning. - Yue Cui 001; Liuyi Yao; Zitao Li; Yaliang Li; Bolin Ding; Xiaofang Zhou 001 (CoRR, 2024)

The Synergy between Data and Multi-Modal Large Language Models: A Survey from Co-Development Perspective. - Zhen Qin 004; Daoyuan Chen; Wenhao Zhang; Liuyi Yao; Yilun Huang 004; Bolin Ding; Yaliang Li; Shuiguang Deng (CoRR, 2024)

Performance-Based Pricing of Federated Learning via Auction. - Zitao Li; Bolin Ding; Liuyi Yao; Yaliang Li; Xiaokui Xiao; Jingren Zhou 001 (Proc. VLDB Endow., 2024)

Is Sharing Neighbor Generator in Federated Graph Learning Safe? - Liuyi Yao; Zhen Wang 036; Yuexiang Xie; Yaliang Li; Weirui Kuang; Daoyuan Chen; Bolin Ding (IEEE Trans. Knowl. Data Eng., 2024)

Enhancing Tool Learning in Large Language Models with Hierarchical Error Checklists. - Yue Cui 001; Liuyi Yao; Shuchang Tao; Weijie Shi; Yaliang Li; Bolin Ding; Xiaofang Zhou 001 (ACL (Findings), 2025)

Safety Layers in Aligned Large Language Models: The Key to LLM Security. - Shen Li; Liuyi Yao; Lan Zhang 002; Yaliang Li (ICLR, 2025)

Diversity as a Reward: Fine-Tuning LLMs on a Mixture of Domain-Undetermined Data. - Zhenqing Ling; Daoyuan Chen; Liuyi Yao; Yaliang Li; Ying Shen 001 (CoRR, 2025)

Efficient Leave-one-out Approximation in LLM Multi-agent Debate Based on Introspection. - Yue Cui 001; Liuyi Yao; Zitao Li; Yaliang Li; Bolin Ding; Xiaofang Zhou 001 (CoRR, 2025)

Security Tensors as a Cross-Modal Bridge: Extending Text-Aligned Safety to Vision in LVLM. - Shen Li; Liuyi Yao; Wujia Niu; Lan Zhang 002; Yaliang Li (CoRR, 2025)