23 citations · 29 across the 11 of their papers we have counts for
5 papers · 1 filter
LLMs Perform Poorly at Concept Extraction in Cyber-security Research Literature
Maxime Würsch, Andrei Kucharavy, Dimitri Percia David +1
The cybersecurity landscape evolves rapidly and poses threats to organizations. To enhance resilience, one needs to track the latest developments and trends in the domain. It has b…
Evolutionary Algorithms in the Light of SGD: Limit Equivalence, Minima Flatness, and Transfer Learning
Andrei Kucharavy, Rachid Guerraoui, Ljiljana Dolamic
Whenever applicable, the Stochastic Gradient Descent (SGD) has shown itself to be unreasonably effective. Instead of underperforming and getting trapped in local minima due to the…
Byzantine-Resilient Learning Beyond Gradients: Distributing Evolutionary Search
Andrei Kucharavy, Matteo Monti, Rachid Guerraoui +1
Modern machine learning (ML) models are capable of impressive performances. However, their prowess is not due only to the improvements in their architecture and training algorithms…
Stochastic Parrots Looking for Stochastic Parrots: LLMs are Easy to Fine-Tune and Hard to Detect with other LLMs
Da Silva Gameiro Henrique, Andrei Kucharavy, Rachid Guerraoui
The self-attention revolution allowed generative language models to scale and achieve increasingly impressive abilities. Such models - commonly referred to as Large Language Models…
Fundamentals of Generative Large Language Models and Perspectives in Cyber-Defense
Andrei Kucharavy, Zachary Schillaci, Loïc Maréchal +6
Generative Language Models gained significant attention in late 2022 / early 2023, notably with the introduction of models refined to act consistently with users' expectations of i…