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pro vyhledávání: '"Kucharavy A"'
With the emergence of widely available powerful LLMs, disinformation generated by large Language Models (LLMs) has become a major concern. Historically, LLM detectors have been touted as a solution, but their effectiveness in the real world is still
Externí odkaz:
http://arxiv.org/abs/2409.03291
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 been demonstrated that standard bibliometrics approaches show their lim
Externí odkaz:
http://arxiv.org/abs/2312.07110
Autor:
Kucharavy, Dmitry1 (AUTHOR) dkucharavy@unistra.fr, Damand, David1 (AUTHOR), Barth, Marc2 (AUTHOR)
Publikováno v:
International Journal of Production Research. Aug2023, Vol. 61 Issue 16, p5411-5435. 25p. 10 Diagrams, 8 Charts, 3 Graphs.
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 batch noise, SGD leverages it to learn to generalize better and find m
Externí odkaz:
http://arxiv.org/abs/2306.09991
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 but also to a drastic increase in computational power used to train t
Externí odkaz:
http://arxiv.org/abs/2304.13540
The self-attention revolution allowed generative language models to scale and achieve increasingly impressive abilities. Such models - commonly referred to as Large Language Models (LLMs) - have recently gained prominence with the general public, tha
Externí odkaz:
http://arxiv.org/abs/2304.08968
Autor:
Kucharavy, Andrei, Schillaci, Zachary, Maréchal, Loïc, Würsch, Maxime, Dolamic, Ljiljana, Sabonnadiere, Remi, David, Dimitri Percia, Mermoud, Alain, Lenders, Vincent
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 interactions with AI (conversational models). Arguably the focal point
Externí odkaz:
http://arxiv.org/abs/2303.12132
The advent of the internet, followed shortly by the social media made it ubiquitous in consuming and sharing information between anyone with access to it. The evolution in the consumption of media driven by this change, led to the emergence of images
Externí odkaz:
http://arxiv.org/abs/2206.00282
This open access book provides cybersecurity practitioners with the knowledge needed to understand the risks of the increased availability of powerful large language models (LLMs) and how they can be mitigated. It attempts to outrun the malicious att
Autor:
Blin, Kevin, Kucharavy, Andrei
In this paper we address the problem of fine-tuned text generation with a limited computational budget. For that, we use a well-performing text generative adversarial network (GAN) architecture - Diversity-Promoting GAN (DPGAN), and attempted a drop-
Externí odkaz:
http://arxiv.org/abs/2108.12275