PublicationsΒΆ

If you find this repository helpful, feel free to cite our publication Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks:

@inproceedings{reimers-2019-sentence-bert,
    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
    author = "Reimers, Nils and Gurevych, Iryna",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
    month = "11",
    year = "2019",
    publisher = "Association for Computational Linguistics",
    url = "http://arxiv.org/abs/1908.10084",
}

If you use one of the multilingual models, feel free to cite our publication Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillation:

@inproceedings{reimers-2020-multilingual-sentence-bert,
    title = "Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillation",
    author = "Reimers, Nils and Gurevych, Iryna",
    booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing",
    month = "11",
    year = "2020",
    publisher = "Association for Computational Linguistics",
    url = "https://arxiv.org/abs/2004.09813",
}

If you use the code for data augmentation, feel free to cite our publication Augmented SBERT: Data Augmentation Method for Improving Bi-Encoders for Pairwise Sentence Scoring Tasks:

@inproceedings{thakur-2020-AugSBERT,
    title = "Augmented {SBERT}: Data Augmentation Method for Improving Bi-Encoders for Pairwise Sentence Scoring Tasks",
    author = "Thakur, Nandan and Reimers, Nils and Daxenberger, Johannes  and Gurevych, Iryna",
    booktitle = "Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies",
    month = jun,
    year = "2021",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/2021.naacl-main.28",
    pages = "296--310",
}

If you use the models for MS MARCO, feel free to cite the paper: The Curse of Dense Low-Dimensional Information Retrieval for Large Index Sizes

@article{reimers-2020-Curse_Dense_Retrieval,
    title = "The Curse of Dense Low-Dimensional Information Retrieval for Large Index Sizes",
    author = "Reimers, Nils and  Gurevych, Iryna", 
    journal= "arXiv preprint arXiv:2012.14210",
    month = "12",
    year = "2020",
    url = "https://arxiv.org/abs/2012.14210",
}

When you use the unsupervised learning example, please have a look at: TSDAE: Using Transformer-based Sequential Denoising Auto-Encoderfor Unsupervised Sentence Embedding Learning:

@article{wang-2021-TSDAE,
    title = "TSDAE: Using Transformer-based Sequential Denoising Auto-Encoderfor Unsupervised Sentence Embedding Learning",
    author = "Wang, Kexin and Reimers, Nils and Gurevych, Iryna", 
    journal= "arXiv preprint arXiv:2104.06979",
    month = "4",
    year = "2021",
    url = "https://arxiv.org/abs/2104.06979",
}

When you use the GenQ learning example, please have a look at: BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models:

@article{thakur-2021-BEIR,
    title = "BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models",
    author = {Thakur, Nandan and Reimers, Nils and R{\"{u}}ckl{\'{e}}, Andreas and Srivastava, Abhishek and Gurevych, Iryna}, 
    journal= "arXiv preprint arXiv:2104.08663",
    month = "4",
    year = "2021",
    url = "https://arxiv.org/abs/2104.08663",
}

Repositories using SentenceTransformers

SentenceTransformers in Articles

In the following you find a (selective) list of articles / applications using SentenceTransformers to do amazing stuff. Feel free to contact me (info@nils-reimers.de) to add you application here.

SentenceTransformers used in Research

SentenceTransformers is used in hundreds of research projects. For a list of publications, see Google Scholar or Semantic Scholar.