Reimers, Nils

Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reimers, N., & Gurevych, I. (2019) · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)

Topic ModelingSentiment Analysis and Opinion Mining

Cited by 12,778

MTEB: Massive Text Embedding Benchmark

Muennighoff, N., Tazi, N., Magne, L., & Reimers, N. (2023) · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics

Topic ModelingMultimodal Machine Learning Applications

Cited by 548

Reporting Score Distributions Makes a Difference: Performance Study of LSTM-networks for Sequence Tagging

Reimers, N., & Gurevych, I. (2017) · Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing

Topic ModelingNatural Language Processing Techniques

Cited by 463

Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reimers, N., & Gurevych, I. (2019) · arXiv

Topic ModelingSentiment Analysis and Opinion Mining

Cited by 343

Classification and Clustering of Arguments with Contextualized Word Embeddings

Reimers, N., Schiller, B., Beck, T., Daxenberger, J., Stab, C., & Gurevych, I. (2019) · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics

Topic ModelingSentiment Analysis and Opinion Mining

Cited by 157

BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models

Thakur, N., Reimers, N., Rücklé, A., Srivastava, A., & Gurevych, I. (2021) · arXiv

Information Retrieval and Search BehaviorTopic Modeling

Cited by 45

Why Comparing Single Performance Scores Does Not Allow to Draw Conclusions About Machine Learning Approaches

Reimers, N., & Gurevych, I. (2018) · arXiv

Machine Learning and Data ClassificationTopic Modeling

Cited by 30