Discourse Parsing with Attention-based Hierarchical Neural Networks
Qi Li, Tianshi Li, and Baobao Chang. "Discourse Parsing with Attention-based Hierarchical Neural Networks." EMNLP. 2016.
Qi Li, Tianshi Li, and Baobao Chang. "Discourse Parsing with Attention-based Hierarchical Neural Networks." EMNLP. 2016.
Miles Q. Li, Benjamin CM Fung, Philippe Charland, and Steven HH Ding. "A Novel and Dedicated Machine Learning Model for Malware Classification." In ICSOFT, pp. 617-628. 2021.
Miles Q. Li and Benjamin CM Fung. "A Novel Neural Network-Based Malware Severity Classification System." In International Conference on Software Technologies, pp. 218-232. Springer, 2021.
Abusitta, Adel, Miles Q. Li, and Benjamin CM Fung. "Malware classification and composition analysis: A survey of recent developments." Journal of Information Security and Applications 59 (2021): 102828.
Li, Miles Q., Benjamin CM Fung, and Philippe Charland. "DyAdvDefender: An instance-based online machine learning model for perturbation-trial-based black-box adversarial defense." Information Sciences (2022).
Miles Q. Li and Benjamin CM Fung. "Interpretable Malware Classification based on Functional Analysis." In ICSOFT, pp. 500-507. 2022.
Li, M. Q., Fung, B. C. M., & Abusitta, A. On the Effectiveness of Interpretable Feedforward Neural Network. In Proceedings of the International Conference on Joint Conference on Neural Networks (IJCNN), pages 1-8, Padova, Italy: IEEE, July 2022.
Miles Q. Li, Benjamin CM Fung, Philippe Charland, and Steven HH Ding. "I-MAD: Interpretable malware detector using Galaxy Transformer." Computers & Security 108 (2021): 102371.
Ashita Diwan, Miles Q. Li, and Benjamin CM Fung. "VDGraph2Vec: Vulnerability Detection in Assembly Code Using Message Passing Neural Networks." In 2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA), pp. 1039-1046. IEEE, 2022.
Miles Q. Li, Benjamin CM Fung, and Ashita Diwan. "A Novel Deep Multi-head Attentive Vulnerable Line Detector." Procedia Computer Science 222 (2023): 35-44.
Abusitta, Adel, Miles Q. Li, and Benjamin CM Fung. "Survey on Explainable AI: Techniques, challenges and open issues." Expert Systems with Applications (2024): 124710.
Miles Q. Li, Benjamin Fung, and Shih-Chia Huang. On the Effectiveness of Incremental Training of Large Language Models. arXiv preprint arXiv:2411.18700 (2024).
Miles Q. Li, Benjamin CM Fung, and Shih-Chia Huang. Training Dynamics of a 1.7B LLaMa Model: A Data-Efficient Approach. In Proceedings of the International Conference on Joint Conference on Neural Networks (IJCNN), pages 1-10, Roma, Italy: IEEE, June 2025.
Miles Q. Li, and Benjamin CM Fung. Security Concerns for Large Language Models: A Survey. Journal of Information Security and Applications 95 (2025): 104284.
Miles Q. Li, Benjamin Fung, Martin Weiss, Pulei Xiong, Khalil Al-Hussaeni, and Claude Fachkha. A Benchmark for Evaluating Outcome-Driven Constraint Violations in Autonomous AI Agents. arXiv preprint arXiv:2512.20798 (2025).
Miles Q. Li, Julien Keutchayan, François Charest, and Benjamin C.M. Fung. GPT-based Self-supervised Anomaly Detection in Command Lines. Journal of Computer Virology and Hacking Techniques, Springer, 2026.
Invited Presentation at IVADO Community of Practice, HEC Montreal, Montreal, Canada
Invited Talk at Kean University, USA
Journal Reviewing
Conference Reviewing
Secondary Reviewing