Papers by Nils Rethmeier
Neighborhood Contrastive Learning for Scientific Document Representations with Citation Embeddings (2022.emnlp-main)
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| Challenge: | Prior work relies on discrete citation relations to generate contrast samples, but discrete ones enforce a hard cut-off to similarity. |
| Approach: | They propose to use nearest neighbor sampling to learn continuous similarity and to sample hard-to-learn negatives and positives by controlling the sampling margin between them. |
| Outcome: | The proposed method outperforms the state-of-the-art on the SciDocs benchmark and can train (or tune) language models sample-efficiently. |
VendorLink: An NLP approach for Identifying & Linking Vendor Migrants & Potential Aliases on Darknet Markets (2023.acl-long)
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| Challenge: | Anonymity on the Darknet allows vendors to stay undetected by using multiple vendor aliases or frequently migrating between markets. |
| Approach: | They propose an NLP-based approach that examines writing patterns to verify, identify, and link unique vendor accounts across text advertisements on seven public Darknet markets. |
| Outcome: | The proposed approach can help law enforcement agencies make more informed decisions by verifying and identifying migrating vendors and their potential aliases on existing and Low-Resource (LR) emerging Darknet markets. |