Social Bayesian Personal Ranking for Missing Data in Implicit Feedback Recommendation. - Yijia Zhang 003; Wanli Zuo; Zhenkun Shi; Lin Yue; Shining Liang (KSEM (1), 2018)

Deep Interpretable Mortality Model for Intensive Care Unit Risk Prediction. - Zhenkun Shi; Weitong Chen 001; Shining Liang; Wanli Zuo; Lin Yue; Sen Wang 001 (ADMA, 2019)

DMMAM: Deep Multi-source Multi-task Attention Model for Intensive Care Unit Diagnosis. - Zhenkun Shi; Wanli Zuo; Weitong Chen 001; Lin Yue; Yuwei Hao; Shining Liang (DASFAA (2), 2019)

A Review of Dataset and Labeling Methods for Causality Extraction. - Jinghang Xu; Wanli Zuo; Shining Liang; Xianglin Zuo (COLING, 2020)

IDDSAM: An Integrated Disease Diagnosis and Severity Assessment Model for Intensive Care Units. - Zhenkun Shi; Wanli Zuo; Shining Liang; Xianglin Zuo; Lin Yue; Xue Li 001 (IEEE Access, 2020)

Joint Personalized Markov Chains with social network embedding for cold-start recommendation. - Yijia Zhang 003; Zhenkun Shi; Wanli Zuo; Lin Yue; Shining Liang; Xue Li 001 (Neurocomputing, 2020)

Reinforced Iterative Knowledge Distillation for Cross-Lingual Named Entity Recognition. - Shining Liang; Ming Gong 001; Jian Pei 001; Linjun Shou; Wanli Zuo; Xianglin Zuo; Daxin Jiang (KDD, 2021)

CalibreNet: Calibration Networks for Multilingual Sequence Labeling. - Shining Liang; Linjun Shou; Jian Pei 001; Ming Gong 001; Wanli Zuo; Daxin Jiang (WSDM, 2021)

Label-aware Multi-level Contrastive Learning for Cross-lingual Spoken Language Understanding. - Shining Liang; Linjun Shou; Jian Pei 001; Ming Gong 001; Wanli Zuo; Xianglin Zuo; Daxin Jiang (EMNLP, 2022)

Multi-level Contrastive Learning for Cross-lingual Spoken Language Understanding. - Shining Liang; Linjun Shou; Jian Pei 001; Ming Gong 001; Wanli Zuo; Xianglin Zuo; Daxin Jiang (CoRR, 2022)

A Word-Granular Adversarial Attacks Framework for Causal Event Extraction. - Yu Zhao; Wanli Zuo; Shining Liang; Xiaosong Yuan; Yijia Zhang 003; Xianglin Zuo (Entropy, 2022)

A multi-level neural network for implicit causality detection in web texts. - Shining Liang; Wanli Zuo; Zhenkun Shi; Sen Wang 001; Junhu Wang; Xianglin Zuo (Neurocomputing, 2022)

Large Language Models are Diverse Role-Players for Summarization Evaluation. - Ning Wu; Ming Gong 001; Linjun Shou; Shining Liang; Daxin Jiang (NLPCC (1), 2023)

Is Bigger and Deeper Always Better? Probing LLaMA Across Scales and Layers. - Nuo Chen 001; Ning Wu; Shining Liang; Ming Gong 001; Linjun Shou; Dongmei Zhang 001; Jia Li 009 (CoRR, 2023)

Dynamic item feature modeling for rating prediction in recommender systems. - Xianglin Zuo; Shining Liang; Xiaosong Yuan; Shuang Yu; Bo Yang (Neurocomputing, 2023)

Towards Truthful Multilingual Large Language Models: Benchmarking and Alignment Strategies. - Weihao Liu; Ning Wu; Wenbiao Ding; Shining Liang; Ming Gong 001; Dongmei Zhang 001 (CoRR, 2024)

Selected Languages are All You Need for Cross-lingual Truthfulness Transfer. - Weihao Liu; Ning Wu; Wenbiao Ding; Shining Liang; Ming Gong 001; Dongmei Zhang 001 (COLING, 2025)

MuDAF: Long-Context Multi-Document Attention Focusing through Contrastive Learning on Attention Heads. - Weihao Liu; Ning Wu; Shiping Yang; Wenbiao Ding; Shining Liang; Ming Gong 001; Dongmei Zhang 001 (CoRR, 2025)

Quantifying the Robustness of Retrieval-Augmented Language Models Against Spurious Features in Grounding Data. - Shiping Yang; Jie Wu; Wenbiao Ding; Ning Wu; Shining Liang; Ming Gong 001; Hengyuan Zhang; Dongmei Zhang 001 (CoRR, 2025)