Miles Q. Li

According to our database, Miles Q. Li authored at least 21 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

GPT-based self-supervised anomaly detection in command lines.

Miles Q. Li, Julien Keutchayan, François Charest, Benjamin C. M. Fung

J. Comput. Virol. Hacking Tech., December, 2026

Taxonomy and Consistency Analysis of Safety Benchmarks for AI Agents.

Miles Q. Li, Benjamin C. M. Fung, Boyang Li, Heba Ismail, Farkhund Iqbal

CoRR, May, 2026

Adaptive Prompt Embedding Optimization for LLM Jailbreaking.

Miles Q. Li, Benjamin C. M. Fung, Boyang Li, Radin Hamidi Rad, Ebrahim Bagheri

CoRR, April, 2026

LLM-as-Judge Framework for Evaluating Tone-Induced Hallucination in Vision-Language Models.

Zhiyuan Jiang, Weihao Hong, Xinlei Guan, Tejaswi Dhandu, Miles Q. Li, Meng Xu, Kuan Huang, Umamaheswara Rao Tida, Bingyu Shen, Daehan Kwak, Boyang Li

CoRR, April, 2026

Toward Accountable AI-Generated Content on Social Platforms: Steganographic Attribution and Multimodal Harm Detection.

Xinlei Guan, David Arosemena, Tejaswi Dhandu, Kuan Huang, Meng Xu, Miles Q. Li, Bingyu Shen, Ruiyang Qin, Umamaheswara Rao Tida, Boyang Li

CoRR, April, 2026

2025

A Benchmark for Evaluating Outcome-Driven Constraint Violations in Autonomous AI Agents.

Miles Q. Li, Benjamin C. M. Fung, Martin Weiss, Pulei Xiong, Khalil Al-Hussaeni, Claude Fachkha

CoRR, December, 2025

Security concerns for Large Language Models: A survey.

Miles Q. Li, Benjamin C. M. Fung

J. Inf. Secur. Appl., 2025

Training Dynamics of a 1.7B LLaMa Model: A Data-Efficient Approach.

Miles Q. Li, Benjamin C. M. Fung, Shih-Chia Huang

Proceedings of the International Joint Conference on Neural Networks, 2025

2024

Survey on Explainable AI: Techniques, challenges and open issues.

Adel Abusitta, Miles Q. Li, Benjamin C. M. Fung

Expert Syst. Appl., 2024

Experience of Training a 1.7B-Parameter LLaMa Model From Scratch.

Miles Q. Li, Benjamin C. M. Fung, Shih-Chia Huang

CoRR, 2024

On the Effectiveness of Incremental Training of Large Language Models.

Miles Q. Li, Benjamin C. M. Fung, Shih-Chia Huang

CoRR, 2024

2023

A Novel Deep Multi-head Attentive Vulnerable Line Detector.

Miles Q. Li, Benjamin C. M. Fung, Ashita Diwan

Proceedings of the International Neural Network Society Workshop on Deep Learning Innovations and Applications, 2023

2022

DyAdvDefender: An instance-based online machine learning model for perturbation-trial-based black-box adversarial defense.

Miles Q. Li, Benjamin C. M. Fung, Philippe Charland

Inf. Sci., 2022

On the Effectiveness of Interpretable Feedforward Neural Network.

Miles Q. Li, Benjamin C. M. Fung, Adel Abusitta

Proceedings of the International Joint Conference on Neural Networks, 2022

Interpretable Malware Classification based on Functional Analysis.

Miles Q. Li, Benjamin C. M. Fung

Proceedings of the 17th International Conference on Software Technologies, 2022

VDGraph2Vec: Vulnerability Detection in Assembly Code using Message Passing Neural Networks.

Ashita Diwan, Miles Q. Li, Benjamin C. M. Fung

Proceedings of the 21st IEEE International Conference on Machine Learning and Applications, 2022

2021

Malware classification and composition analysis: A survey of recent developments.

Adel Abusitta, Miles Q. Li, Benjamin C. M. Fung

J. Inf. Secur. Appl., 2021

<i>I-MAD</i>: Interpretable malware detector using Galaxy Transformer.

Miles Q. Li, Benjamin C. M. Fung, Philippe Charland, Steven H. H. Ding

Comput. Secur., 2021

A Novel and Dedicated Machine Learning Model for Malware Classification.

Miles Q. Li, Benjamin C. M. Fung, Philippe Charland, Steven H. H. Ding

Proceedings of the 16th International Conference on Software Technologies, 2021

A Novel Neural Network-Based Malware Severity Classification System.

Miles Q. Li, Benjamin C. M. Fung

Proceedings of the Software Technologies - 16th International Conference, 2021

2019

I-MAD: A Novel Interpretable Malware Detector Using Hierarchical Transformer.

Miles Q. Li, Benjamin C. M. Fung, Philippe Charland, Steven H. H. Ding

CoRR, 2019