8 citations · 14 across the 20 of their papers we have counts for
20 papers · 1 filter
Compositional Multilingual and Behavioral Attribute Steering
Hyun Gu Kang, Daniil Gurgurov, Tanja Baeumel +2
This study examines the compositionality of steering vectors for language and behavioral control in large language models. Focusing on language, jailbreak, and conciseness, we inve…
Separating Syntax from Language: A Mechanistic Account of Translation in Multilingual LLMs
Mikhail Sonkin, Tanja Baeumel, Daniil Gurgurov +2
Multilingual large language models (mLLMs) achieve strong performance in machine translation, yet our understanding of the mechanisms by which they transform representations from o…
A Sovereign, Open-Source Foundation Model for German and English
Soofi-Team, :, Benedikt Droste +30
We present Soofi S 30B-A3B, a sovereign, open-source Mixture-of-Experts (MoE) hybrid Mamba Transformer foundation model for German and English. Its hybrid design activates only 3B…
Want Better Synthetic Data? Steer It: Activation Steering for Low-Resource Language Generation
Jan Cegin, Daniil Gurgurov, Yusser Al Ghussin +1
Large language models (LLMs) have become an effective tool for synthetic data generation, including for low-resource languages, where generated data can improve downstream task per…
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…
From Weights to Activations: Is Steering the Next Frontier of Adaptation?
Simon Ostermann, Daniil Gurgurov, Tanja Baeumel +4
Post-training adaptation of language models is commonly achieved through parameter updates or input-based methods such as fine-tuning, parameter-efficient adaptation, and prompting…
ReasonXL: A Large-Scale Corpus for Language-Specific Reasoning in LLMs
Daniil Gurgurov, Tom Röhr, Sebastian von Rohrscheidt +3
Despite advances in multilingual capabilities, most large language models (LLMs) remain English-centric in their training and, crucially, in the reasoning traces they produce: even…
CLaS-Bench: A Cross-Lingual Alignment and Steering Benchmark
Daniil Gurgurov, Yusser Al Ghussin, Tanja Baeumel +5
Understanding and controlling the behavior of large language models (LLMs) is an increasingly important topic in multilingual NLP. Beyond prompting or fine-tuning, , i.e.,~manipula…
Sparse Subnetwork Enhancement for Underrepresented Languages in Large Language Models
Daniil Gurgurov, Tanja Baeumel, Josef van Genabith +1
Large language models (LLMs) exhibit substantial performance disparities across languages, particularly between high- and low-resource settings. We propose a framework for improvin…
Modular Arithmetic: Language Models Solve Math Digit by Digit
Tanja Baeumel, Daniil Gurgurov, Yusser al Ghussin +2
While recent work has begun to uncover the internal strategies that Large Language Models (LLMs) employ for simple arithmetic tasks, a unified understanding of their underlying mec…
Multilingual Political Views of Large Language Models: Identification and Steering
Daniil Gurgurov, Katharina Trinley, Ivan Vykopal +3
Large language models (LLMs) are increasingly used in everyday tools and applications, raising concerns about their potential influence on political views. While prior research has…
Language Arithmetics: Towards Systematic Language Neuron Identification and Manipulation
Daniil Gurgurov, Katharina Trinley, Yusser Al Ghussin +3
Large language models (LLMs) exhibit strong multilingual abilities, yet the neural mechanisms behind language-specific processing remain unclear. We analyze language-specific neuro…
On Multilingual Encoder Language Model Compression for Low-Resource Languages
Daniil Gurgurov, Michal Gregor, Josef van Genabith +1
In this paper, we combine two-step knowledge distillation, structured pruning, truncation, and vocabulary trimming for extremely compressing multilingual encoder-only language mode…
Small Models, Big Impact: Efficient Corpus and Graph-Based Adaptation of Small Multilingual Language Models for Low-Resource Languages
Daniil Gurgurov, Ivan Vykopal, Josef van Genabith +1
Low-resource languages (LRLs) face significant challenges in natural language processing (NLP) due to limited data. While current state-of-the-art large language models (LLMs) stil…
GrEmLIn: A Repository of Green Baseline Embeddings for 87 Low-Resource Languages Injected with Multilingual Graph Knowledge
Daniil Gurgurov, Rishu Kumar, Simon Ostermann
Contextualized embeddings based on large language models (LLMs) are available for various languages, but their coverage is often limited for lower resourced languages. Using LLMs f…
Image-to-LaTeX Converter for Mathematical Formulas and Text
Daniil Gurgurov, Aleksey Morshnev
In this project, we train a vision encoder-decoder model to generate LaTeX code from images of mathematical formulas and text. Utilizing a diverse collection of image-to-LaTeX data…
Adapting Multilingual LLMs to Low-Resource Languages with Knowledge Graphs via Adapters
Daniil Gurgurov, Mareike Hartmann, Simon Ostermann
This paper explores the integration of graph knowledge from linguistic ontologies into multilingual Large Language Models (LLMs) using adapters to improve performance for low-resou…
Multilingual Large Language Models and Curse of Multilinguality
Daniil Gurgurov, Tanja Bäumel, Tatiana Anikina
Multilingual Large Language Models (LLMs) have gained large popularity among Natural Language Processing (NLP) researchers and practitioners. These models, trained on huge datasets…