2 citations · 2 across the 2 of their papers we have counts for
7 papers · 1 filter
Finetuning with Scientific Data Increases Hallucinations: A Multi-domain Factuality Evaluation of LLMs
Raia Abu Ahmad, Nikolas Rauscher, Ekaterina Borisova +3
Large language models (LLMs) are increasingly used to communicate and explain scientific concepts, yet their tendency to hallucinate poses significant risks in this high stakes use…
SciLaD: A Large-Scale, Transparent, Reproducible Dataset for Natural Scientific Language Processing
Luca Foppiano, Sotaro Takeshita, Pedro Ortiz Suarez +6
SciLaD is a novel, large-scale dataset of scientific language constructed entirely using open-source frameworks and publicly available data sources. It comprises a curated English…
Teuken-7B-Base & Teuken-7B-Instruct: Towards European LLMs
Mehdi Ali, Michael Fromm, Klaudia Thellmann +38
We present two multilingual LLMs, Teuken 7B-base and Teuken 7B-instruct, designed to embrace Europe's linguistic diversity by supporting all 24 official languages of the European U…
Table Understanding and (Multimodal) LLMs: A Cross-Domain Case Study on Scientific vs. Non-Scientific Data
Ekaterina Borisova, Fabio Barth, Nils Feldhus +5
Tables are among the most widely used tools for representing structured data in research, business, medicine, and education. Although LLMs demonstrate strong performance in downstr…
Multilingual European Language Models: Benchmarking Approaches and Challenges
Fabio Barth, Georg Rehm
The breakthrough of generative large language models (LLMs) that can solve different tasks through chat interaction has led to a significant increase in the use of general benchmar…
Are Multilingual Language Models an Off-ramp for Under-resourced Languages? Will we arrive at Digital Language Equality in Europe in 2030?
Georg Rehm, Annika Grützner-Zahn, Fabio Barth
Large language models (LLMs) demonstrate unprecedented capabilities and define the state of the art for almost all natural language processing (NLP) tasks and also for essentially…