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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 11 of 11 1 MaartenGr/BERTopic: v0.9.2 ... Grootendorst, Maarten; Reimers, Nils. - : Zenodo, 2021 BASE Show details 2 MaartenGr/BERTopic: v0.8.1 ... Grootendorst, Maarten; Reimers, Nils. - : Zenodo, 2021 BASE Show details 3 TSDAE: Using Transformer-based Sequential Denoising Auto-Encoder for Unsupervised Sentence Embedding Learning ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Iryna; Reimers, Nils. - : Underline Science Inc., 2021 BASE Show details 4 The Curse of Dense Low-Dimensional Information Retrieval for Large Index Sizes ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; ., Iryna; Reimers, Nils. - : Underline Science Inc., 2021 BASE Show details 5 BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models ... Thakur, Nandan; Reimers, Nils; Rücklé, Andreas. - : arXiv, 2021 BASE Show details 6 GPL: Generative Pseudo Labeling for Unsupervised Domain Adaptation of Dense Retrieval ... Wang, Kexin; Thakur, Nandan; Reimers, Nils. - : arXiv, 2021 BASE Show details 7 Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillation ... Reimers, Nils; Gurevych, Iryna. - : arXiv, 2020 BASE Show details 8 Revisiting Joint Modeling of Cross-document Entity and Event Coreference Resolution ... Barhom, Shany; Shwartz, Vered; Eirew, Alon; Bugert, Michael; Reimers, Nils; Dagan, Ido. - : arXiv, 2019 Abstract: Recognizing coreferring events and entities across multiple texts is crucial for many NLP applications. Despite the task's importance, research focus was given mostly to within-document entity coreference, with rather little attention to the other variants. We propose a neural architecture for cross-document coreference resolution. Inspired by Lee et al (2012), we jointly model entity and event coreference. We represent an event (entity) mention using its lexical span, surrounding context, and relation to entity (event) mentions via predicate-arguments structures. Our model outperforms the previous state-of-the-art event coreference model on ECB+, while providing the first entity coreference results on this corpus. Our analysis confirms that all our representation elements, including the mention span itself, its context, and the relation to other mentions contribute to the model's success. ... : ACL 2019 ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://arxiv.org/abs/1906.01753 https://dx.doi.org/10.48550/arxiv.1906.01753 BASE Hide details 9 Optimal Hyperparameters for Deep LSTM-Networks for Sequence Labeling Tasks ... Reimers, Nils; Gurevych, Iryna. - : arXiv, 2017 BASE Show details 10 DARIAH-DKPro-Wrapper Output Format (DOF) Specification Jannidis, Fotis; Pernes, Stefan (VerfasserIn); Pielström, Steffen (VerfasserIn). - : GOEDOC, Dokumenten- und Publikationsserver der Georg-August-Universität Göttingen, 2016. : Niedersächsische Staats- und Universitätsbibliothek Göttingen, 2016 BASE Show details 11 GermEval-2014: Nested Named Entity Recognition with Neural Networks Schnober, Carsten; Kim, Jungi; Gurevych, Iryna. - 2014 BASE Show details

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