At a glance
- Opportunity
- Master's thesis
- Location
- Darmstadt, DE, 64295
- Funding / pay
- Not specified by the organization
- Eligibility
- Check the qualifications in the official posting
Project description
The Fraunhofer Institute for Secure Information Technology SIT is one of the leading research and development institutions for cybersecurity in Germany and Europe and is part of ATHENE, the national research center for applied cybersecurity. ATHENE is a collaboration between the Fraunhofer Society, TU Darmstadt, Hochschule Darmstadt, and Goethe University Frankfurt. Our common goal: to make the world of tomorrow safer. Be part of change LLMs have gained significant attention recently due to their remarkable capabilities. A similar, yet less explored field focuses on text-to-image (T2I) model architectures. Since a picture is worth more than a thousand words, one can assume that T2I models possess at least as many capabilities as text-to-text models (T2T). Therefore, it is important to subject these models to an "alignment" process. In T2T models, some neurones in the architecture are repurposed as safety neurones. To better understand the alignment process, the locations of safety neurones in both architectures should be compared.Objective: The work aims to investigate the localisations of safety neurones in T2I models and compare them with T2T models. For this purpose, the proposed approaches for the localisation of safety neurones from T2T models will be adapted and implemented for T2I models. Finally, results regarding the localisation and significance of the neurones are analysed to highlight similarities and differences in the architectures.Results: The results of this work aim to conceptualise the differences in model architectures for LLM security research. Since T2I models receive less attention, it is important to motivate further research on these models. For this purpose, a comprehensive comparison of different architectures and their associated safety neurones will be conducted as part of the work. The results are verified by a targeted deactivation of the identified neurones and then compared with randomly deactivated neurones.What you do with us: Researching and implementing novel machine learning approaches that enhance the security of LLMs Self-critical evaluation of the obtained results Presenting the results Preparing a project report in the form of a master's thesis
Funding and compensation
Compensation not specified. See the original posting for amounts, duration and conditions.
Eligibility and application requirements
Review the qualifications, research interests and required documents in the description above. The employer or university's original posting is the source for complete eligibility requirements.
Before you apply
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How to apply
Submit your application through Fraunhofer's official application process. Apply early as a closing date has not been specified.
Source and listing information
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