Master Thesis: Long Context Extension for Public Sector Document Retrieval

As Sweden's national center for applied AI, we're on a mission to accelerate the use of AI to benefit our society, our competitiveness, and everyone living in Sweden. We drive impactful initiatives in areas such as healthcare, energy, and public services while pushing the boundaries of AI research in fields such as natural language processing, machine learning and AI security. Join us in harnessing the untapped value of AI to drive innovation and create sustainable value for Sweden.

We are now looking for a master thesis student to join our team.

Project Background and Problem Statement

AI Sweden is developing context length extensions for the Prelude 9B model. Simultaneously, Skatteverket requires "Labb/experiment" Proof-of-Concepts (POCs) for utilizing LLMs with their internal documents (Väg 1). This thesis investigates:

• How efficiently can Prelude 9B be extended to 32k or 64k (or longer) tokens for Swedish administrative RAG tasks without catastrophic forgetting of its core reasoning and language modeling capabilities?

Who we’re looking for

We are seeking curious, self-driven MSc students eager to work at the frontier of open-weight European AI research (LLMs). You thrive on empirical discovery, design rigorous experiments, and let data challenge your assumptions.

• Ongoing Master’s studies in Computer Science, Data Science, Machine Learning, Engineering Physics, or a related quantitative field.

• Proficiency in Python and hands-on experience with modern deep learning frameworks (PyTorch, Hugging Face ecosystem).

• Familiarity with LLM post-training alignment (e.g., SFT, DPO, RLHF/RLVR) or context-extension, alongside comfort running distributed GPU training in Linux/HPC environments.

At AI Sweden, we are committed to building diverse and inclusive teams. Some positions may be subject to export control regulations, which means that specific requirements may apply.

If you have any questions or thoughts, don’t hesitate to contact

Birger Moëll, Senior Research Scientist
Niclas Hertzberg, AI Engineer

AI Sweden does not accept unsolicited support and kindly ask not to be contacted by any advertisement agents, recruitment agencies or manning companies.

References

[1] Peng, B., et al., "YaRN: Efficient Context Window Extension of Large Language Models," ICLR 2024.

[2] Ding, Y., et al., "LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens," arXiv 2024.