14 citations · 36 across the 5 of their papers we have counts for
8 papers
SindBERT, the Sailor: Charting the Seas of Turkish NLP
Raphael Schmitt, Stefan Schweter
Transformer models have revolutionized NLP, yet many morphologically rich languages remain underrepresented in large-scale pre-training efforts. With SindBERT, we set out to chart…
BLOOM: A 176B-Parameter Open-Access Multilingual Language Model
BigScience Workshop, :, Teven Le Scao +391
Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to wi…
hmBERT: Historical Multilingual Language Models for Named Entity Recognition
Stefan Schweter, Luisa März, Katharina Schmid +1
Compared to standard Named Entity Recognition (NER), identifying persons, locations, and organizations in historical texts constitutes a big challenge. To obtain machine-readable c…
Entities, Dates, and Languages: Zero-Shot on Historical Texts with T0
Francesco De Toni, Christopher Akiki, Javier de la Rosa +4
In this work, we explore whether the recently demonstrated zero-shot abilities of the T0 model extend to Named Entity Recognition for out-of-distribution languages and time periods…
Data Centric Domain Adaptation for Historical Text with OCR Errors
Luisa März, Stefan Schweter, Nina Poerner +2
We propose new methods for in-domain and cross-domain Named Entity Recognition (NER) on historical data for Dutch and French. For the cross-domain case, we address domain shift by…
FLERT: Document-Level Features for Named Entity Recognition
Stefan Schweter, Alan Akbik
Current state-of-the-art approaches for named entity recognition (NER) typically consider text at the sentence-level and thus do not model information that crosses sentence boundar…
German's Next Language Model
Branden Chan, Stefan Schweter, Timo Möller
In this work we present the experiments which lead to the creation of our BERT and ELECTRA based German language models, GBERT and GELECTRA. By varying the input training data, mod…
Towards Robust Named Entity Recognition for Historic German
Stefan Schweter, Johannes Baiter
Recent advances in language modeling using deep neural networks have shown that these models learn representations, that vary with the network depth from morphology to semantic rel…