10 citations · 30 across the 5 of their papers we have counts for
5 papers
VendorLink: An NLP approach for Identifying & Linking Vendor Migrants & Potential Aliases on Darknet Markets
Vageesh Saxena, Nils Rethmeier, Gijs Van Dijck +1
The anonymity on the Darknet allows vendors to stay undetected by using multiple vendor aliases or frequently migrating between markets. Consequently, illegal markets and their con…
Neighborhood Contrastive Learning for Scientific Document Representations with Citation Embeddings
Malte Ostendorff, Nils Rethmeier, Isabelle Augenstein +2
Learning scientific document representations can be substantially improved through contrastive learning objectives, where the challenge lies in creating positive and negative train…
A Primer on Contrastive Pretraining in Language Processing: Methods, Lessons Learned and Perspectives
Nils Rethmeier, Isabelle Augenstein
Modern natural language processing (NLP) methods employ self-supervised pretraining objectives such as masked language modeling to boost the performance of various application task…
Data-Efficient Pretraining via Contrastive Self-Supervision
Nils Rethmeier, Isabelle Augenstein
For natural language processing `text-to-text' tasks, the prevailing approaches heavily rely on pretraining large self-supervised models on increasingly larger `task-external' data…
TX-Ray: Quantifying and Explaining Model-Knowledge Transfer in (Un-)Supervised NLP
Nils Rethmeier, Vageesh Kumar Saxena, Isabelle Augenstein
While state-of-the-art NLP explainability (XAI) methods focus on explaining per-sample decisions in supervised end or probing tasks, this is insufficient to explain and quantify mo…