3 citations · 4 across the 12 of their papers we have counts for
40 papers
A Sovereign, Open-Source Foundation Model for German and English
The Soofi-Team, Soofi-Team, : +31
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…
Generative Large Language Models in Automated Fact-Checking: A Survey
Ivan Vykopal, Matúš Pikuliak, Simon Ostermann +1
The rapid spread of false and misleading information on online platforms poses a growing societal challenge, overwhelming the capacity of manual fact-checking and increasing the de…
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…
Enhancing AI Interpretability with Localised Architectures
Ian Seet, Jonas Bozenhard, Simon Ostermann
Recent advances in generative AI, especially powerful Large Language Models (LLMs), raise concerns over the interpretability, safety and sustainability of these large and opaque AI…
Macro: Enhancing Multilingual Counterfactual Explanations through Alignment-as-Preference Optimization
Yilong Wang, Qianli Wang, Bohao Chu +3
Self-generated counterfactual explanations (SCEs) are minimally modified inputs (minimality) generated by large language models (LLMs) that flip their own predictions (validity), o…
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…