🧑‍🔬 Who cites Larraitz Uria

308 citations of their works from 308 papers of our library (of the 149,439 whose bibliographies we read) · 32 with a page here, the most cited first · ← Larraitz Uria

1. Sentence-BERT: Sentence Embeddings using Siamese BERT-NetworksConference on Empirical Methods in Natural Language Processing (EMNLP)Nils Reimers, Iryna Gurevych2019 · 17,096 citations
2. SimCSE: Simple Contrastive Learning of Sentence EmbeddingsConference on Empirical Methods in Natural Language Processing (EMNLP)Tianyu Gao, Xingcheng Yao, Danqi Chen2021 · 3,942 citations
3. SemEval-2017 Task 1: Semantic Textual Similarity Multilingual and Crosslingual Focused EvaluationInternational Workshop on Semantic Evaluation (SemEval)Daniel Cer, Mona Diab, Eneko Agirre, et al.2017 · 1,828 citations
4. MTEB: Massive Text Embedding BenchmarkConference of the European Chapter of the Association for Computational Linguistics (EACL)Niklas Muennighoff, Nouamane Tazi, Loïc Magne, et al.2022 · 1,032 citations
5. C-Pack: Packed Resources For General Chinese EmbeddingsInternational ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)Shitao Xiao, Zheng Liu, Peitian Zhang, et al.2023 · 922 citations
6. On the Sentence Embeddings from Pre-trained Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Bohan Li, Hao Zhou, Junxian He, et al.2020 · 833 citations
7. SentEval: An Evaluation Toolkit for Universal Sentence RepresentationsLanguage Resources and Evaluation Conference (LREC)Alexis Conneau, Douwe Kiela2018 · 747 citations
8. ConSERT: A Contrastive Framework for Self-Supervised Sentence Representation TransferAnnual Meeting of the Association for Computational Linguistics (ACL)Yuanmeng Yan, Rumei Li, Sirui Wang, et al.2021 · 647 citations
9. Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text ModelsFindings of the Association for Computational LinguisticsJianmo Ni, Gustavo Hernandez Abrego, Noah Constant, et al.2021 · 583 citations
10. DeCLUTR: Deep Contrastive Learning for Unsupervised Textual RepresentationsAnnual Meeting of the Association for Computational Linguistics (ACL)John Giorgi, Osvald Nitski, Bo Wang, et al.2021 · 516 citations
11. ParaNMT-50M: Pushing the Limits of Paraphrastic Sentence Embeddings with Millions of Machine TranslationsAnnual Meeting of the Association for Computational Linguistics (ACL)John Wieting, Kevin Gimpel2018 · 504 citations
12. A Continuously Growing Dataset of Sentential ParaphrasesConference on Empirical Methods in Natural Language Processing (EMNLP)Wuwei Lan, Siyu Qiu, Hua He, et al.2017 · 267 citations
13. Generating Datasets with Pretrained Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Timo Schick, Hinrich Schutze2021 · 254 citations
14. Charagram: Embedding Words and Sentences via Character n-gramsConference on Empirical Methods in Natural Language Processing (EMNLP)John Wieting, Mohit Bansal, Kevin Gimpel, et al.2016 · 242 citations
15. Self-Guided Contrastive Learning for BERT Sentence RepresentationsAnnual Meeting of the Association for Computational Linguistics (ACL)Taeuk Kim, Kang Min Yoo, Sang-goo Lee2021 · 234 citations
16. Beyond BLEU: Training Neural Machine Translation with Semantic SimilarityAnnual Meeting of the Association for Computational Linguistics (ACL)John Wieting, Taylor Berg-Kirkpatrick, Kevin Gimpel, et al.2019 · 223 citations
17. An Unsupervised Sentence Embedding Method by Mutual Information MaximizationConference on Empirical Methods in Natural Language Processing (EMNLP)Yan Zhang, Ruidan He, Zuozhu Liu, et al.2020 · 213 citations
18. Self-training Improves Pre-training for Natural Language UnderstandingConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Jingfei Du, Edouard Grave, Beliz Gunel, et al.2021 · 172 citations
19. Fast, Effective, and Self-Supervised: Transforming Masked Language Models into Universal Lexical and Sentence EncodersConference on Empirical Methods in Natural Language Processing (EMNLP)Fangyu Liu, Ivan Vulić, Anna Korhonen, et al.2021 · 147 citations
20. MMTEB: Massive Multilingual Text Embedding BenchmarkarXiv:2502.13595Kenneth Enevoldsen, Isaac Chung, Imene Kerboua, et al.2025 · 103 citations
21. AnglE-optimized Text EmbeddingsarXiv:2309.12871Xianming Li, Jing Li2023 · 103 citations
22. A Large-Scale Comparison of Historical Text Normalization SystemsMarcel Bollmann2019 · 99 citations
23. ParaAMR: A Large-Scale Syntactically Diverse Paraphrase Dataset by AMR Back-TranslationKuan-Hao Huang, Varun Iyer, I-Hung Hsu, et al.2023 · 24 citations
24. LIM-LIG at SemEval-2017 Task1: Enhancing the Semantic Similarity for Arabic Sentences with Vectors WeightingInternational Workshop on Semantic Evaluation (SemEval)El Moatez Billah Nagoudi, Jérémy Ferrero, Didier Schwab2017 · 21 citations
25. Semi-supervised Contextual Historical Text NormalizationPeter Makarov, Simon Clematide2020 · 12 citations
26. Token Prepending: A Training-Free Approach for Eliciting Better Sentence Embeddings from LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Yuchen Fu, Zifeng Cheng, Zhiwei Jiang, et al.2025 · 10 citations
27. UBC: Cubes for English Semantic Textual Similarity and Supervised Approaches for Interpretable STSInternational Workshop on Semantic Evaluation (SemEval)Eneko Agirre, Aitor Gonzalez-Agirre, Iñigo Lopez-Gazpio, et al.2015 · 10 citations
28. Edition 2.0 of the PARSEME shared task on multilingual identification and paraphrasing of multiword expressionsWorkshop on Multiword Expressions (MWE)Manon Scholivet, Agata Savary, Carlos Ramisch, et al.2026 · 9 citations
29. Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time SteeringAnnual Meeting of the Association for Computational Linguistics (ACL)Zifeng Cheng, Zhonghui Wang, Yuchen Fu, et al.2025 · 8 citations
30. Few-Shot and Zero-Shot Learning for Historical Text NormalizationMarcel Bollmann, Natalia Korchagina, Anders Søgaard2019 · 2 citations
31. Explainable Semantic Textual Similarity via Dissimilar Span DetectionLanguage Resources and Evaluation Conference (LREC)Diego Miguel Lozano, Daryna Dementieva, Alexander Fraser2026 · 1 citation
32. AEA: Adaptive Expert Allocation Improves Sentence Embeddings from Mixture-of-Experts LLMAnnual Meeting of the Association for Computational Linguistics (ACL)Shufan Yang, Zifeng Cheng, Zhiwei Jiang, et al.2026

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