14 papers
news-crawler-LM: A Small Long-Context Model For High-Quality News Crawling
Pascal Stolzenburg, Jonas Golde, Max Dallabetta +1
Extracting structured content from news pages remains challenging due to heterogeneous HTML layouts, inconsistent markup, and substantial boilerplate such as navigation elements an…
Repetition over Diversity: High-Signal Data Filtering for Sample-Efficient German Language Modeling
Ansar Aynetdinov, Patrick Haller, Alan Akbik
Recent research has shown that filtering massive English web corpora into high-quality subsets significantly improves training efficiency. However, for high-resource non-English la…
Beyond Marginal Distributions: A Framework to Evaluate the Representativeness of Demographic-Aligned LLMs
Tristan Williams, Franziska Weeber, Sebastian Padó +1
Large language models are increasingly used to represent human opinions, values, or beliefs, and their steerability towards these ideals is an active area of research. Existing wor…
What Matters in Linearizing Language Models? A Comparative Study of Architecture, Scale, and Task Adaptation
Patrick Haller, Jonas Golde, Alan Akbik
Linearization has emerged as a strategy for developing efficient language models (LMs). Starting from an existing Transformer-based LM, linearization replaces the attention compone…
What Matters When Building Universal Multilingual Named Entity Recognition Models?
Jonas Golde, Patrick Haller, Alan Akbik
Recent progress in universal multilingual named entity recognition (NER) has been driven by multilingual transformer models, task-specific architectures, custom loss functions, and…
FiNERweb: Datasets and Artifacts for Scalable Multilingual Named Entity Recognition
Jonas Golde, Patrick Haller, Alan Akbik
Recent multilingual named entity recognition (NER) work has shown that large language models (LLMs) can provide effective synthetic supervision, yet such datasets have mostly appea…