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Bell Labs Internship on Cross-Model Feature Transfer (PhD) en ST DO EICS NW Ops & Tools (L05)

ST DO EICS NW Ops & Tools (L05) · Antwerp, Bélgica · Onsite

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An increasing body of work has demonstrated that behavior in neural networks can often be explained and controlled through linear operations on their hidden activations. Model steering, for instance, is a technique where a specific target concept is elicited in the predictions of a generative model by adding a concept vector to its activations

Recent work suggests that these concept vectors can be transferred between models.  In this PhD internship, you will investigate the feasibility of cross-model feature transfer for improving the performance and reliability of machine learning models.
 

Responsibilities

  • You will review scientific literature

  • You will design and implement a cross-model feature transfer method(s)

  • Evaluate the effectiveness of the proposed technique(s) on representative problems

  • Consolidate your research in a scientific publication and/or a patent application

Location: Antwerp (Belgium)  

Qualifications

  • Student enrolled in Ph.D. Computer Science/Engineering in Machine Learning 

  • Strong programming skills in Python  

  • Language skills: English  

  • Experience with representation engineering, mechanistic interpretability, or explainable AI is a big plus.

  • A strong publication record is a big plus.  

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