Maxime Dassen

Hi, I'm Maxime (she/her). I am a PhD student in Artificial Intelligence/Computer Science at the IRLab of the University of Amsterdam, where I am fortunate to be advised by Andrew Yates and Evangelos Kanoulas.

My research aims to understand how foundation models acquire, represent, and manipulate information across modalities, and how that understanding can be utilized to build AI systems that are more reliable, interpretable, controllable, and efficient.

In 2025 I was a Visiting PhD Student at the Johns Hopkins University HLTCOE as part of the SCALE 2025 program, and will return for SCALE 2026 to work on multimodal RAG.

Ultimately, I believe that understanding these internal mechanisms is essential for building AI systems that people can genuinely trust.

Last updated at May 1st 2026

profile photo

Selected Research

I'm interested in machine learning, deep learning, generative AI, and multimodal learning. Some papers are highlighted.

ECIR '2026
FACTUM: Mechanistic Detection of Citation Hallucination in Long-Form RAG
Maxime Dassen, Rebecca Kotula, Kenton Murray, Andrew Yates,
Dawn Lawrie, Efsun Kayi, James Mayfield, Kevin Duh
European Conference on Information Retrieval (ECIR), 2026
arXiv code

We introduce FACTUM, a mechanistic framework that detects citation hallucinations in long-form RAG by identifying scale-dependent signatures in transformer pathways, outperforming state-of-the-art baselines by up to 37.5%.


Template adjusted from this website.