3 citations · 3 across the 1 of their papers we have counts for
3 papers
cs.CL2021
Benchmarking down-scaled (not so large) pre-trained language models
M. Aßenmacher, P. Schulze, C. Heumann
Large Transformer-based language models are pre-trained on corpora of varying sizes, for a different number of steps and with different batch sizes. At the same time, more fundamen…
cs.CL2021
Re-Evaluating GermEval17 Using German Pre-Trained Language Models
M. Aßenmacher, A. Corvonato, C. Heumann
The lack of a commonly used benchmark data set (collection) such as (Super-)GLUE (Wang et al., 2018, 2019) for the evaluation of non-English pre-trained language models is a severe…
cs.CL2020★ 3 cited
Pre-trained language models as knowledge bases for Automotive Complaint Analysis
V. D. Viellieber, M. Aßenmacher
Recently it has been shown that large pre-trained language models like BERT (Devlin et al., 2018) are able to store commonsense factual knowledge captured in its pre-training corpu…