3 citations · 3 across the 3 of their papers we have counts for
5 papers
Intelligent Learning Rate Distribution to reduce Catastrophic Forgetting in Transformers
Philip Kenneweg, Alexander Schulz, Sarah Schröder +1
Pretraining language models on large text corpora is a common practice in natural language processing. Fine-tuning of these models is then performed to achieve the best results on…
Debiasing Sentence Embedders through Contrastive Word Pairs
Philip Kenneweg, Sarah Schröder, Alexander Schulz +1
Over the last years, various sentence embedders have been an integral part in the success of current machine learning approaches to Natural Language Processing (NLP). Unfortunately…
Neural Architecture Search for Sentence Classification with BERT
Philip Kenneweg, Sarah Schröder, Barbara Hammer
Pre training of language models on large text corpora is common practice in Natural Language Processing. Following, fine tuning of these models is performed to achieve the best res…
Targeted Visualization of the Backbone of Encoder LLMs
Isaac Roberts, Alexander Schulz, Luca Hermes +1
Attention based Large Language Models (LLMs) are the state-of-the-art in natural language processing (NLP). The two most common architectures are encoders such as BERT, and decoder…
Semantic Properties of cosine based bias scores for word embeddings
Sarah Schröder, Alexander Schulz, Fabian Hinder +1
Plenty of works have brought social biases in language models to attention and proposed methods to detect such biases. As a result, the literature contains a great deal of differen…