Fleshman, W., Raff, E., Zak, R., McLean, M., & Nicholas, C. (2018). Static Malware Detection & Subterfuge: Quantifying the Robustness of Machine Learning and Current Anti-Virus. In The 13th International Conference on Malicious and Unwanted Software (MALWARE).
Fleshman, W., Raff, E., Sylvester, J., Forsyth, S., & McLean, M. (2019). Non-Negative Networks Against Adversarial Attacks. In AAAI-2019 Workshop on Artificial Intelligence for Cyber Security.
B., B., Fleshman, W., H., K., Kaliszewski, R., R.,S. (2020). Deception and the Strategy of Influence. In National Security Agency’s The Next Wave, Vol. 23, No. 1.
Raff, E., Fleshman, W., Zak, R., Anderson, H. S., Filar, B., & McLean, M. (2021). Classifying Sequences of Extreme Length with Constant Memory Applied to Malware Detection. In The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI).
William Fleshman and Benjamin Van Durme, Toucan: Token-Aware Character Level Language Modeling, 2023.
William Fleshman, Aleem Khan, Marc Marone, and Benjamin Van Durme, AdapterSwap: Continuous Training of LLMs with Data Removal and Access-Control Guarantees, 2024.
William Fleshman and Benjamin Van Durme, RE-Adapt: Reverse Engineered Adaptation of Large Language Models, 2024.
William Fleshman and Benjamin Van Durme, RE-AdaptIR: Improving Information Retrieval through Reverse Engineered Adaptation, 2024.
Talk at UC San Francisco, Department of Testing, San Francisco, California
Tutorial at UC-Berkeley Institute for Testing Science, Berkeley CA, USA
Talk at London School of Testing, London, UK
Conference proceedings talk at Testing Institute of America 2014 Annual Conference, Los Angeles, CA