Nils Rethmeier | DeepAI

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∙ 05/04/2023

VendorLink: An NLP approach for Identifying Linking Vendor Migrants Potential Aliases on Darknet Markets

The anonymity on the Darknet allows vendors to stay undetected by using ...

9 Vageesh Saxena, et al. ∙

∙ 02/14/2022

Neighborhood Contrastive Learning for Scientific Document Representations with Citation Embeddings

Learning scientific document representations can be substantially improv...

10 Malte Ostendorff, et al. ∙

∙ 02/25/2021

A Primer on Contrastive Pretraining in Language Processing: Methods, Lessons Learned and Perspectives

Modern natural language processing (NLP) methods employ self-supervised ...

9 Nils Rethmeier, et al. ∙

∙ 10/02/2020

Long-Tail Zero and Few-Shot Learning via Contrastive Pretraining on and for Small Data

For natural language processing (NLP) tasks such as sentiment or topic c...

0 Nils Rethmeier, et al. ∙

∙ 07/27/2020

EffiCare: Better Prognostic Models via Resource-Efficient Health Embeddings

Recent medical prognostic models adapted from high data-resource fields ...

0 Nils Rethmeier, et al. ∙

∙ 01/10/2020

MoRTy: Unsupervised Learning of Task-specialized Word Embeddings by Autoencoding

Word embeddings have undoubtedly revolutionized NLP. However, pre-traine...

0 Nils Rethmeier, et al. ∙

∙ 12/02/2019

TX-Ray: Quantifying and Explaining Model-Knowledge Transfer in (Un-)Supervised NLP

While state-of-the-art NLP explainability (XAI) methods focus on supervi...

20 Nils Rethmeier, et al. ∙

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