105 citations · 245 across the 61 of their papers we have counts for
63 papers
DFKI-MLT at SemEval-2026 TASK 7: Steering Multilingual Models Towards Cultural Knowledge
Yusser Al Ghussin, Daniil Gurgurov, Yasser Hamidullah +3
Large language models (LLMs) are increasingly used across diverse linguistic and cultural contexts, yet their cultural knowledge remains uneven across regions and languages. We pre…
Multilingual Steering by Design: Multilingual Sparse Autoencoders and Principled Layer Selection
Yusser Al Ghussin, Daniil Gurgurov, Tanja Baeumel +3
Sparse autoencoders (SAEs) enable feature-level mechanistic interpretability and activation steering in large language models (LLMs), but SAE-based language control remains unrelia…
The Latin Substrate: How Language Models Represent and Mediate Script Choice
Daniil Gurgurov, Alan Saji, Katharina Trinley +2
Many languages are written in multiple scripts, requiring large language models (LLMs) to generate equivalent linguistic content in distinct orthographic forms. While prior work su…
DualFact+: A Multimodal Fact Verification Framework for Procedural Video Understanding
Cennet Oguz, Yasser Hamidullah, Josef van Genabith +1
We introduce DualFact, a dual-layer, multimodal factuality evaluation framework for procedural video captioning. DualFact separates factual correctness into conceptual facts, captu…
Why Does Reinforcement Learning Generalize? A Feature-Level Mechanistic Study of Post-Training in Large Language Models
Dan Shi, Zhuowen Han, Simon Ostermann +3
Reinforcement learning (RL)-based post-training often improves the reasoning performance of large language models (LLMs) beyond the training domain, while supervised fine-tuning (S…
Disentangling Mathematical Reasoning in LLMs: A Methodological Investigation of Internal Mechanisms
Tanja Baeumel, Josef van Genabith, Simon Ostermann
Large language models (LLMs) have demonstrated impressive capabilities, yet their internal mechanisms for handling reasoning-intensive tasks remain underexplored. To advance the un…