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FRFraunhofer-Gesellschaft

Master's Thesis: Localisation of Safety Neurones in Text2Image Models(m/w/x)

Darmstadt
Full-timeInternshipOn-site

Researching neuron localization in T2I models, adapting T2T approaches at an application-oriented research institute. Machine Learning knowledge (transformers) and Python (Pytorch) skills required. Independent work schedule management.

Requirements

  • Knowledge in Machine Learning (training, inference, transformer architectures)
  • Desirable knowledge in ML security
  • Good Python skills (Pytorch)
  • Scientific interest
  • Interest in current research projects

Tasks

  • Investigate safety neuron localizations in T2I models.
  • Compare T2I neuron localizations with T2T models.
  • Adapt T2T safety neuron localization approaches for T2I models.
  • Implement adapted localization approaches for T2I models.
  • Analyze neuron localization and significance results.
  • Highlight architectural similarities and differences.
  • Conceptualize model architectural differences for LLM security research.
  • Motivate further research on T2I models.
  • Conduct a comprehensive comparison of architectures and safety neurons.
  • Verify results through targeted neuron deactivation.
  • Compare results with randomly deactivated neurons.
  • Research and implement novel machine learning approaches to enhance LLM security.
  • Critically evaluate obtained results.
  • Present research results.
  • Prepare a project report as a master's thesis.

Education

  • Currently in higher educationOR
  • Bachelor's degreeOR
  • Master's degree

Languages

  • EnglishBusiness Fluent

Tools & Technologies

  • Python
  • Pytorch
  • transformer architectures

Benefits

Flexible Working

  • Independent work schedule management
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