Publications

Journal Articles

• [J21] Zhou, C., Liu, S., Kang, D., Li, Z., & Liu, Y. (2026). Streaming platforms vs. theaters: Navigating the strategic choices of film distributors in channel selection. Electronic Commerce Research and Applications, 78, 101623. [SCIE/SSCI, JCR-Q1, Impact factor = 6.8]

• [J20] Jiang, Y., Teng, X., C. Cho, W., Wang, H., Zhao, M., Ma, J., Meng, X., Xiao, H., Lu, Y., Cheung, A. L., Li, Z.,... & Cai, J. (2026). Bridging multi-omics to routine precision oncology: Biologically informed knowledge transfer for precision pCR prediction in neoadjuvant immunotherapy. Journal of Clinical Oncology, 44(16_suppl), e12569. [SCIE, JCR-Q1, Impact factor = 44.7]

• [J19] Li, Z.^*, Li, X., Li, J., Xie, H., Wang, F. L., & Li, Q. (2026). LS-BiLLMs: Label supervised bi-directional large language models for token-and sequence-level information extraction. Information Processing & Management, 63(4), 104568. [SCIE/SSCI, JCR-Q1, Impact factor = 8.1]

• [J18] Chen, X., Li, Z.^*, Xie, H., Wang, J., Li, Q., & Hung, K. (2025). Recognizing conditional causal relationships about emotions and their corresponding conditions. In Web Intelligence (Vol. 23, No. 4, pp. 579-595). [ESCI, JCR-Q4, Impact factor = 0.4]

• [J17] Liu, X., Cao, J., Yu, W., Li, Z., Wang, Y., Gu, H., & Vuković, D. B. (2025). Multi-feature Adaptive-fusion Enhanced graph neural Network for open-set node classification. Neurocomputing, 640, 130238. [SCIE, JCR-Q1, Impact factor = 6.7]

• [J16] Li, Z.^*, Wang, Z., Wang, W., Hung, K., Xie, H., & Wang, F. L. (2025). Retrieval-augmented generation for educational application: A systematic survey. Computers and Education: Artificial Intelligence, 8, 100417. [ESCI, JCR-Q1, Impact factor = 23.4]

• [J15] Chen, X., Xie, H., Li, Z., Zhang, H., Tao, X., & Wang, F. L. (2025). Sentiment analysis for stock market research: A bibliometric study. Natural Language Processing Journal, 10, 100125. [Scopus]

• [J14] Chen, X., Zou, D., Xie, H., Cheng, G., Li, Z., & Wang, F. L. (2025). Automatic classification of online learner reviews via fine-tuned BERTs. International Review of Research in Open and Distributed Learning, 26(1), 57-79. [SSCI, JCR-Q1, Impact factor = 4.5]

• [J13] Wu, B., Hu, Y., Yu, X., Sun, M., Xie, H., Li, Z., & Wang, M. (2023). How do secondary students engage in complex problem-solving processes in a STEM project?. Knowledge Management & E-Learning. [ESCI, JCR-Q1, Impact factor = 2.5]

• [J12] Chen, X., Xie, H., Li, Z., Zhang, D., Cheng, G., Wang, F. L., Dai, H. N., & Li, Q. (2023). Leveraging deep learning for automatic literature screening in intelligent bibliometrics. International Journal of Machine Learning and Cybernetics, 14(4), 1483-1525. [SCI, JCR-Q1, Impact factor = 5.6]

• [J11] Xu, L., Xie, H., Li, Z., Wang, F. L., Wang, W., & Li, Q. (2023). Contrastive learning models for sentence representations. ACM Transactions on Intelligent Systems and Technology, 14(4), 1-34. [SCI, JCR-Q1, Impact factor = 10.5]

• [J10] Chen, X., Li, Q., Li, Z.^*, Xie, H., Wang, F. L., & Wang, J. (2022). A reinforcement learning based two-stage model for emotion cause pair extraction. IEEE Transactions on Affective Computing, 14(3), 1779-1790. [SCI, JCR-Q1, Impact factor = 11.2]

• [J09] Li, Z., Li, X., Xie, H., Wang, F. L., Leng, M., Li, Q., & Tao, X. (2023). A novel dropout mechanism with label extension schema toward text emotion classification. Information Processing & Management, 60(2), 103173. [SCI, JCR-Q1, Impact factor = 8.6]

• [J08] Chen, X., Xie, H., Li, Z., Cheng, G., Leng, M., & Wang, F. L. (2023). Information fusion and artificial intelligence for smart healthcare: a bibliometric study. Information Processing & Management, 60(1), 103113. [SCI, JCR-Q1, Impact factor = 8.6]

• [J07] Zhang, H., Li, Z.^*, Xie, H., Lau, R. Y., Cheng, G., Li, Q., & Zhang, D. (2022). Leveraging statistical information in fine-grained financial sentiment analysis. World Wide Web, 25(2), 513-531. [SCI, JCR-Q1, Impact factor = 3.7]

• [J06] Chen, X., Xie, H., Cheng, G., & Li, Z. (2022). A decade of sentic computing: topic modeling and bibliometric analysis. Cognitive Computation, 14(1), 24-47. [SCI, JCR-Q1, Impact factor = 5.4]

• [J05] Li, Z., Chen, X., Xie, H., Li, Q., Tao, X., & Cheng, G. (2021). EmoChannel-SA: exploring emotional dependency towards classification task with self-attention mechanism. World Wide Web, 24, 2049-2070. [SCI, JCR-Q1, Impact factor = 3.7]

• [J04] Chen, X., Xie, H., Li, Z., & Cheng, G. (2021). Topic analysis and development in knowledge graph research: A bibliometric review on three decades. Neurocomputing, 461, 497-515. [SCI, JCR-Q1, Impact factor = 6.0]

• [J03] Chen, X., Xie, H., Wang, J., Li, Z., Cheng, G., Wong, M. L., & Wang, F. L. (2021). A bibliometric review of soft computing for recommender systems and sentiment analysis. IEEE Transactions on Artificial Intelligence, 3(5), 642-656. [Scopus, CiteScore = 7.0, a new IEEE Transactions]

• [J02] Li, Z., Xie, H., Cheng, G., & Li, Q. (2021). Word-level emotion distribution with two schemas for short text emotion classification. Knowledge-Based Systems, 227, 107163. [SCI, JCR-Q1, Impact factor = 8.8]

• [J01] Li, Z., Xie, H., Xu, G., Li, Q., Leng, M., & Zhou, C. (2021). Towards purchase prediction: A transaction-based setting and a graph-based method leveraging price information. Pattern Recognition, 113, 107824. [SCI, JCR-Q1, Impact factor = 8.0]

Conference Proceedings

• [C24] Jiang, Y., Ding, H., Chen, H., Lan, J., Teng, X., Cheng, G. W., Mao, Y., Li, Z.... & Cai, J. (2026). Decoding the Alzheimer’s Continuum: Interpretable Multi-gate Routing for Diagnosis and Transition Prediction. In International Conference on Medical Image Computing and Computer-Assisted Intervention (pp. 172-182). Cham: Springer Nature Switzerland. [CCF-B]

• [C23] Ma, X., Li, Z.^*, Dong, C., Shao, D., & Liu, X. (2026). QueueBreak: A Trace-to-Diagnosis Pipeline for Tail Latency in Agentic LLM Services. In 2026 IEEE International Conference on Web Services (ICWS) (pp. 1083-1090). IEEE. [CCF-B]

• [C22] Zhang, H., Xu, W., Zhang, P., Li, Z.b>, Luo, Y., & Guo, H. (2026, July). Monitoring Building Aging and Damage with Diffusion Transformers: A Survey. In 2026 International Symposium on Machine Learning and Media Computing (MLMC) (pp. 1-6). IEEE.

• [C21] Ma, X., Li, Z.^*, Dong, C., Fang, K., & Shao, D. (2026). GreenTune: Energy-Efficient Low-Rank Tuning of LLMs with ThreeE Evaluation under 4-/8-bit Quantization. In Proceedings of the ACM Web Conference 2026 (pp. 9397-9408). [CCF-A]

• [C20] Li, Z.^*, Li, Y., Xie, H., & Qin, S. J. (2025). Condambigqa: A benchmark and dataset for conditional ambiguous question answering. In Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing (pp. 2269-2288). [CCF-B]

• [C19] Jiang, Y., Li, Z.^*, Chen, X., Xie, H., & Cai, J. (2025). U-MLLA: A Cognitive-Inspired Enhancement of Linear Attention for Medical Image Segmentation. In Chinese Conference on Pattern Recognition and Computer Vision (PRCV) (pp. 76-90).

• [C18] Wang, Z., Li, Z.^*, Xie, H., Wang, M., Wu, B., & Hu, Y. (2025). Context-Aware Multi-label Classification for Collaborative Problem Solving Dialogue Analysis. In International Conference on Blended Learning (pp. 279-290).

• [C17] Wang, Z., Li, Z.^*, Hung, K., Wang, W., & Au Yeung, S. K. (2025). Self-Explanation-Augmented Generation for Natural Language Inference. In International Conference on Neural Computing for Advanced Applications (pp. 88-99).

• [C16] Li, X., Li, Z., Li, J., Xie, H., & Li, Q. (2025). ESE: Espresso sentence embeddings. In International Conference on Learning Representations (Vol. 2025, pp. 38912-38925). [CCF-A]

• [C15] Leung, C. H. J., Yi, Y., Kuai, L., Li, Z., Yeung, S. K. A., Lee, K. W. J., ... & Hung, K. (2024). RAG for Question-Answering for Vocal Training Based on Domain Knowledge Base. In 2024 11th International Conference on Behavioural and Social Computing (BESC) (pp. 1-6). IEEE.

• [C14] Chen, X., Li, Z., Zou, D., Wang, F. L., Xie, H., & Wong, L. P. (2024). Leveraging deep learning for classifying learner-generated course evaluation texts. In International Conference on Blended Learning (pp. 311-321).

• [C13] Kwok, R. Y. K., Au Yeung, S. K., Li, Z.^*, & Hung, K. (2023). Cantonese to written chinese translation via huggingface translation pipeline. In Proceedings of the 2023 7th International Conference on Natural Language Processing and Information Retrieval (pp. 77-84).

• [C12] Han, W., Li, Z.^*, Xie, H., Hung, K., & Wang, M. (2023). Beyond scores: a novel method for predicting student performance based on rank and positional embedding. In 2023 10th International Conference on Behavioural and Social Computing (BESC) (pp. 1-6). IEEE.

• [C11] Jiang, Y., Li, F., Li, Z.^*, Liu, Z., & Wang, Z. (2023). Enhancing continuous sign language recognition with self-attention and MediaPipe Holistic. In 2023 8th International Conference on Instrumentation, Control, and Automation (ICA) (pp. 97-102). IEEE. [Outcome of an undergraduate final-year project]

• [C10] Wang, Z., Liu, Z., Li, Z.^*, Jiang, Y., & Li, F. (2023). American sign language alphabet recognition with YOLOv5 enhanced by MediaPipe Hands. In 2023 8th International Conference on Instrumentation, Control, and Automation (ICA) (pp. 103-108). IEEE. [Outcome of an undergraduate final-year project]

• [C09] Li, X., Li, Z.^*, Luo, X., Xie, H., Zhao, Y., Wang, F. L., & Li, Q. (2023). Recurrent attention networks for long-text modeling. In Findings of the Association for Computational Linguistics: ACL 2023 (pp. 3006-3019). ACL. [CCF-A]

• [C08] Li, Z., Xie, H., Wang, F. L., Wang, W., & Chow, M. K. (2022). Identify students at risk based on behavioural patterns in continuous assessment. In 2022 9th International Conference on Behavioural and Social Computing (BESC) (pp. 1-6). IEEE. [Best Paper Runner-up Awards]

• [C07] Li, Z., Xie, H., Wang, M., Wu, B., & Hu, Y. (2022). Automatic coding of collective creativity dialogues in collaborative problem solving based on deep learning models. In International Conference on Blended Learning (pp. 123-134). Cham: Springer International Publishing.

• [C06] Li, Z., Li, X., Xie, H., Li, Q., & Tao, X. (2021). A label extension schema for improved text emotion classification. In IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (pp. 32-39).

• [C05] Li, X., Li, Z.^*, Xie, H., & Li, Q. (2021). Merging statistical feature via adaptive gate for improved text classification. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 35, No. 15, pp. 13288-13296). [CCF-A]

• [C04] Li, Z.,, Chen, X., Xie, H., Li, Q., & Tao, X. (2020). Emochannelattn: Exploring emotional construction towards multi-class emotion classification. In 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) (pp. 242-249). IEEE. [Best Paper Awards]

• [C03] Li, Z., Xie, H., Zhao, Y., & Li, Q. (2019). Incorporating latent space correlation coefficients to collaborative filtering. In 2019 IEEE 35th International Conference on Data Engineering Workshops (ICDEW) (pp. 155-160). IEEE.

• [C02] Ren, D., Cai, Y., Chan, W. H., & Li, Z. (2018). A clustering based adaptive sequence-to-sequence model for dialogue systems. In 2018 IEEE International Conference on Big Data and Smart Computing (BigComp) (pp. 775-781). IEEE.

• [C01] Li, Z., Zou, D., Xie, H., Wang, F. L., & Chang, M. (2018). Enhancing information literacy in Hong Kong higher education through game-based learning. In The 22nd Global Chinese Conference on Computers in Education: Conference Proceedings (pp. 595-598). South China Normal University.

Preprints

• [P05] Li, X., Li, Z., Lee, T. F. A., Li, J., Xie, H., & Li, Q. (2026). ShadowPEFT: Shadow Network for Parameter-Efficient Fine-Tuning. arXiv preprint arXiv:2604.19254.

• [P04] Jiang, Y., Ding, H., Chen, H., Lan, J., Teng, X., Cheng, G. W. Y., Li, Z., Xie, H., Yoo, J. S., & Cai, J. (2025). M³AD: Multi-task multi-gate mixture of experts for Alzheimer’s disease diagnosis with conversion pattern modeling. arXiv:2508.01819v1

• [P03] Lan, J., Ding, H., Chen, H., Jiang, Y., Ng, N. C., Cheng, G. W., Li, Z., ... & Yoo, J. S. (2025). Contrastive Multi-Task Learning with Solvent-Aware Augmentation for Drug Discovery. arXiv preprint arXiv:2508.01799.

• [P02] Li, Z., Li, X., Liu, Y., Xie, H., Li, J., Wang, F. L., Li, Q. & Zhong, X. (2023). Label supervised LLaMA finetuning. arXiv preprint arXiv:2310.01208.

• [P01] Li, X., Li, Z.^*, Zhao, Y., Xie, H., & Li, Q. (2020). Incorporating effective global information via adaptive gate attention for text classification. arXiv preprint arXiv:2002.09673.