5 papers
Distilling Knowledge from Large Language Models into Lightweight Reinforcement Learning Agents for Autonomous Cyber Operations
Konur Tholl, François Rivest, Mariam El Mezouar +2
Autonomous Cyber Operations (ACO) are increasingly important for defending enterprise networks as cyber threats continue to evolve in sophistication. ACO applications commonly empl…
Large Language Model Integration with Reinforcement Learning to Augment Decision-Making in Autonomous Cyber Operations
Konur Tholl, François Rivest, Mariam El Mezouar +2
Reinforcement Learning (RL) has shown great potential for autonomous decision-making in the cybersecurity domain, enabling agents to learn through direct environment interaction. H…
Towards Production-Worthy Simulation for Autonomous Cyber Operations
Konur Tholl, Mariam El Mezouar, Adrian Taylor +1
Simulated environments have proven invaluable in Autonomous Cyber Operations (ACO) where Reinforcement Learning (RL) agents can be trained without the computational overhead of emu…
A Comparative Evaluation of Teacher-Guided Reinforcement Learning Techniques for Autonomous Cyber Operations
Konur Tholl, Mariam El Mezouar, Ranwa Al Mallah
Autonomous Cyber Operations (ACO) rely on Reinforcement Learning (RL) to train agents to make effective decisions in the cybersecurity domain. However, existing ACO applications re…
NeoBERT: A Next-Generation BERT
Lola Le Breton, Quentin Fournier, Mariam El Mezouar +2
Recent innovations in architecture, pre-training, and fine-tuning have led to the remarkable in-context learning and reasoning abilities of large auto-regressive language models su…