Abstract
Control vectors have recently gained popularity as a method for steering transformer-based generative language models. This paper contributes to this path of research by evaluating the robustness of these control vectors in multi- and cross-lingual question-answering settings mimicking the real-world deployment scenario, where models are expected to generate answers to challenging questions. We present a set of experiments to demonstrate that a control vector approach can be used to shift the output of a generative language model from one language to another, and to exercise stylistic control of the output across languages. Overall, we find that the control vector approach offers a relatively lightweight and effective path for developing methods to control the output of multilingual language models with multiple design choices affecting the real-world control performance.- Anthology ID:
- 2025.nejlt-1.1
- Volume:
- Northern European Journal of Language Technology, Volume 11
- Month:
- December
- Year:
- 2025
- Address:
- Linköping, Sweden
- Editor:
- Marcel Bollmann
- Venue:
- NEJLT
- SIG:
- Publisher:
- Linköping University Electronic Press
- Note:
- Pages:
- 1–26
- Language:
- URL:
- https://preview.aclanthology.org/nameupper/2025.nejlt-1.1/
- DOI:
- 10.3384/nejlt.2000-1533.2025.5888
- Cite (ACL):
- Julius Leino and Jussi Karlgren. 2025. Controlling Language and Style of Multi-lingual Generative Language Models with Control Vectors. Northern European Journal of Language Technology, 11:1–26.
- Cite (Informal):
- Controlling Language and Style of Multi-lingual Generative Language Models with Control Vectors (Leino & Karlgren, NEJLT 2025)
- PDF:
- https://preview.aclanthology.org/nameupper/2025.nejlt-1.1.pdf