Review on cyber-physical systems. - Yang Liu; Yu Peng; Bailing Wang; Sirui Yao; Zihe Liu (IEEE CAA J. Autom. Sinica, 2017)

VisuaLife: A Campaign Aiming to Visualise Air Pollution in the Form of T-shirts Displayed in an Exhibition. - Jack Solomon; Lorenzo Bellucci; Yunsheng Su; Zihe Liu; Mihaela Dimitrova (CHI Extended Abstracts, 2018)

A Registration and Change Detection Algorithm Based on Pre-and Post-Strike Image. - Zihe Liu; Yuhui Wang (ISCID (2), 2018)

Generating commit messages from diffs using pointer-generator network. - Qin Liu 004; Zihe Liu; Hongming Zhu; Hongfei Fan; Bowen Du 002; Yu Qian (MSR, 2019)

Multi-Cue and Temporal Attention for Person Recognition in Videos. - Wenzhe Wang; Bin Wu 001; Fangtao Li; Zihe Liu (PRCV (2), 2020)

CS-Siam: Siamese-Type Network Tracking Method with Added Cluster Segmentation. - Xuming Han; Qi Qin; Yuwei Wang; Yihang Zhang; Hanlin Li; Zihe Liu (ADMA, 2021)

Recognizing Characters and Relationships from Videos via Spatial-Temporal and Multimodal Cues. - Chenyu Cao; Chenghao Yan; Fangtao Li; Zihe Liu; Zheng Wang; Bin Wu 001 (ICBK, 2021)

Dual-Waveform Emotion Recognition Model for Conversations. - Jiayi Zhang; Zihe Liu; Peihang Liu; Bin Wu 001 (ICME, 2021)

Relation-aware Hierarchical Attention Framework for Video Question Answering. - Fangtao Li; Ting Bai; Chenyu Cao; Zihe Liu; Chenghao Yan; Bin Wu 001 (ICMR, 2021)

Social Relation Analysis from Videos via Multi-entity Reasoning. - Chenghao Yan; Zihe Liu; Fangtao Li; Chenyu Cao; Zheng Wang; Bin Wu 001 (ICMR, 2021)

Frame Aggregation and Multi-modal Fusion Framework for Video-Based Person Recognition. - Fangtao Li; Wenzhe Wang; Zihe Liu; Haoran Wang; Chenghao Yan; Bin Wu 001 (MMM (1), 2021)

Self-supervised Group Meiosis Contrastive Learning for EEG-Based Emotion Recognition. - Haoning Kan; Jiale Yu; Jiajin Huang; Zihe Liu; Haiyan Zhou (CoRR, 2022)

A Multimodal Approach for Multiple-Relation Extraction in Videos. - Zihe Liu; Weiying Hou; Jiayi Zhang; Chenyu Cao; Bin Wu 001 (Multim. Tools Appl., 2022)

Self-supervised group meiosis contrastive learning for EEG-based emotion recognition. - Haoning Kan; Jiale Yu; Jiajin Huang; Zihe Liu; Heqian Wang; Haiyan Zhou (Appl. Intell., 2023)

Towards Multi-Relational Multi-Hop Reasoning over Dense Temporal Knowledge Graphs. - Jian Liu 032; Zihe Liu; Xueqiang Lyu; Peng Jin; Jinan Xu (ACL (Findings), 2024)

A Behavior-Aware Approach for Deep Reinforcement Learning in Non-stationary Environments without Known Change Points. - Zihe Liu; Jie Lu 001; Guangquan Zhang 001; Junyu Xuan (IJCAI, 2024)

Functional Wasserstein Variational Policy Optimization. - Junyu Xuan; Mengjing Wu; Zihe Liu; Jie Lu 001 (UAI, 2024)

Location of safflower filaments picking points in complex environment based on improved Yolov5 algorithm. - Xiaorong Wang; Jianping Zhou; Yan Xu; Chao Cui; Zihe Liu; Jinrong Chen (Comput. Electron. Agric., 2024)

NGD converges to less degenerate solutions than SGD. - Moosa Saghir; N. R. Raghavendra; Zihe Liu; Evan Ryan Gunter (CoRR, 2024)

Textualized Agent-Style Reasoning for Complex Tasks by Multiple Round LLM Generation. - Chen Liang; Zhifan Feng; Zihe Liu; Wenbin Jiang 002; Jinan Xu; Yufeng Chen 005; Yong Wang (CoRR, 2024)

Efficient Model Compression for Bayesian Neural Networks. - Diptarka Saha; Zihe Liu; Feng Liang (CoRR, 2024)

Deep Reinforcement Learning in Nonstationary Environments With Unknown Change Points. - Zihe Liu; Jie Lu 001; Junyu Xuan; Guangquan Zhang 001 (IEEE Trans. Cybern., 2024)

Multi-Stage LLM Fine-Tuning with a Continual Learning Setting. - Changhao Guan; Chao Huang; Hongliang Li; You Li; Ning Cheng; Zihe Liu; Yufeng Chen 005; Jinan Xu; Jian Liu 032 (NAACL (Findings), 2025)

A Tutorial on Neural Network-Based Solvers for Hyperbolic Conservation Laws: Supervised vs. Unsupervised Learning, and Applications to Traffic Modeling. - Alexi Canesse; Zhe Fu; Nathan Lichtlé; Hossein Nick Zinat Matin; Zihe Liu; Maria Laura Delle Monache; Alexandre M. Bayen (NeuS, 2025)

Research on low-loss and high-efficiency picking sequence planning of safflower-filaments based on improved deep reinforcement learning. - Xiaorong Wang; Zhou Jianping; Xu Yan; Zihe Liu (Comput. Electron. Agric., 2025)

Learning Latent and Changing Dynamics in Real Non-Stationary Environments. - Zihe Liu; Jie Lu 001; Junyu Xuan; Guangquan Zhang 001 (IEEE Trans. Knowl. Data Eng., 2025)

Reinforcement Learning Optimization for Large-Scale Learning: An Efficient and User-Friendly Scaling Library. - Weixun Wang; Shaopan Xiong; Gengru Chen; Wei Gao; Sheng Guo 005; Yancheng He; Ju Huang; Jiaheng Liu; Zhendong Li; Xiaoyang Li; Zichen Liu; Haizhou Zhao; et al. (CoRR, 2025)

A Robust Incomplete Multimodal Low-Rank Adaptation Approach for Emotion Recognition. - Xinkui Zhao; Jinsong Shu; Yangyang Wu; Guanjie Cheng; Zihe Liu; Naibo Wang; Shuiguang Deng; Zhongle Xie; Jianwei Yin (CoRR, 2025)