15 citations · 54 across the 15 of their papers we have counts for
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cs.LG2023★ 4 cited
Tokenizer Choice For LLM Training: Negligible or Crucial?
Mehdi Ali, Michael Fromm, Klaudia Thellmann +18
The recent success of Large Language Models (LLMs) has been predominantly driven by curating the training dataset composition, scaling of model architectures and dataset sizes and…
cs.CL2023★ 5 cited
AspectCSE: Sentence Embeddings for Aspect-based Semantic Textual Similarity Using Contrastive Learning and Structured Knowledge
Tim Schopf, Emanuel Gerber, Malte Ostendorff +1
Generic sentence embeddings provide a coarse-grained approximation of semantic textual similarity but ignore specific aspects that make texts similar. Conversely, aspect-based sent…
cs.CL2023★ 15 cited
Efficient Language Model Training through Cross-Lingual and Progressive Transfer Learning
Malte Ostendorff, Georg Rehm
Most Transformer language models are primarily pretrained on English text, limiting their use for other languages. As the model sizes grow, the performance gap between English and…