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Nils Reimers
Nils Reimers
Director of Machine Learning, cohere.ai
Verified email at nils-reimers.de - Homepage
Title
Cited by
Cited by
Year
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
N Reimers, I Gurevych
Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019
111032019
Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillation
N Reimers, I Gurevych
EMNLP 2020, 2020
9342020
Beir: A heterogenous benchmark for zero-shot evaluation of information retrieval models
N Thakur, N Reimers, A Rücklé, A Srivastava, I Gurevych
arXiv preprint arXiv:2104.08663, 2021
6592021
Reporting Score Distributions Makes a Difference: Performance Study of LSTM-networks for Sequence Tagging
N Reimers, I Gurevych
Proceedings of the 2017 Conference on Empirical Methods in Natural Language …, 2017
5002017
Optimal Hyperparameters for Deep LSTM-Networks for Sequence Labeling Tasks
N Reimers, I Gurevych
arXiv preprint arXiv:1707.06799, 2017
4192017
MTEB: Massive text embedding benchmark
N Muennighoff, N Tazi, L Magne, N Reimers
arXiv preprint arXiv:2210.07316, 2022
2362022
Classification and Clustering of Arguments with Contextualized Word Embeddings
N Reimers, B Schiller, T Beck, J Daxenberger, C Stab, I Gurevych
ACL 2019, 2019
2222019
Augmented SBERT: Data Augmentation Method for Improving Bi-Encoders for Pairwise Sentence Scoring Tasks
N Thakur, N Reimers, J Daxenberger, I Gurevych
NAACL 2021, 2020
2012020
Adapterdrop: On the efficiency of adapters in transformers
A Rücklé, G Geigle, M Glockner, T Beck, J Pfeiffer, N Reimers, I Gurevych
arXiv preprint arXiv:2010.11918, 2020
1942020
Tsdae: Using transformer-based sequential denoising auto-encoder for unsupervised sentence embedding learning
K Wang, N Reimers, I Gurevych
arXiv preprint arXiv:2104.06979, 2021
1742021
Efficient few-shot learning without prompts
L Tunstall, N Reimers, UES Jo, L Bates, D Korat, M Wasserblat, O Pereg
arXiv preprint arXiv:2209.11055, 2022
1252022
GPL: Generative pseudo labeling for unsupervised domain adaptation of dense retrieval
K Wang, N Thakur, N Reimers, I Gurevych
arXiv preprint arXiv:2112.07577, 2021
1212021
Revisiting joint modeling of cross-document entity and event coreference resolution
S Barhom, V Shwartz, A Eirew, M Bugert, N Reimers, I Dagan
arXiv preprint arXiv:1906.01753, 2019
1122019
Task-oriented intrinsic evaluation of semantic textual similarity
N Reimers, P Beyer, I Gurevych
Proceedings of COLING 2016, the 26th International Conference on …, 2016
822016
Retrieve fast, rerank smart: Cooperative and joint approaches for improved cross-modal retrieval
G Geigle, J Pfeiffer, N Reimers, I Vulić, I Gurevych
Transactions of the Association for Computational Linguistics 10, 503-521, 2022
572022
Germeval-2014: Nested named entity recognition with neural networks
N Reimers, J Eckle-Kohler, C Schnober, J Kim, I Gurevych
Workshop Proceedings of the 12th Edition of the KONVENS Conference, 117-120, 2014
542014
Why comparing single performance scores does not allow to draw conclusions about machine learning approaches
N Reimers, I Gurevych
arXiv preprint arXiv:1803.09578, 2018
512018
The curse of dense low-dimensional information retrieval for large index sizes
N Reimers, I Gurevych
arXiv preprint arXiv:2012.14210, 2020
502020
Temporal Anchoring of Events for the TimeBank Corpus
N Reimers, N Dehghani, I Gurevych
Annual Meeting of the Association for Computational Linguistics (ACL 2016), 2016
432016
Alternative weighting schemes for elmo embeddings
N Reimers, I Gurevych
arXiv preprint arXiv:1904.02954, 2019
312019
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