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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 – 9 of 9 1 What you can cram into a single \$&!#* vector: Probing sentence embeddings for linguistic properties Conneau, Alexis; Kruszewski, German; Lample, Guillaume... In: ACL 2018 - 56th Annual Meeting of the Association for Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-01898412 ; ACL 2018 - 56th Annual Meeting of the Association for Computational Linguistics, Jul 2018, Melbourne, Australia. pp.2126-2136 (2018) BASE Show details 2 XNLI: Evaluating Cross-lingual Sentence Representations ... Conneau, Alexis; Lample, Guillaume; Rinott, Ruty. - : arXiv, 2018 BASE Show details 3 What you can cram into a single vector: Probing sentence embeddings for linguistic properties ... Conneau, Alexis; Kruszewski, German; Lample, Guillaume; Barrault, Loïc; Baroni, Marco. - : arXiv, 2018 Abstract: Although much effort has recently been devoted to training high-quality sentence embeddings, we still have a poor understanding of what they are capturing. "Downstream" tasks, often based on sentence classification, are commonly used to evaluate the quality of sentence representations. The complexity of the tasks makes it however difficult to infer what kind of information is present in the representations. We introduce here 10 probing tasks designed to capture simple linguistic features of sentences, and we use them to study embeddings generated by three different encoders trained in eight distinct ways, uncovering intriguing properties of both encoders and training methods. ... : ACL 2018 ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://arxiv.org/abs/1805.01070 https://dx.doi.org/10.48550/arxiv.1805.01070 BASE Hide details 4 Fader Networks: Manipulating Images by Sliding Attributes Lample, Guillaume; Zeghidour, Neil; Usunier, Nicolas... In: 31st Conference on Neural Information Processing Systems (NIPS 2017) ; https://hal.archives-ouvertes.fr/hal-02275215 ; 31st Conference on Neural Information Processing Systems (NIPS 2017), Dec 2017, Long Beach, CA, United States. pp.5969-5978 (2017) BASE Show details 5 Word Translation Without Parallel Data ... Conneau, Alexis; Lample, Guillaume; Ranzato, Marc'Aurelio. - : arXiv, 2017 BASE Show details 6 Massively Multilingual Word Embeddings ... Ammar, Waleed; Mulcaire, George; Tsvetkov, Yulia. - : arXiv, 2016 BASE Show details 7 Polyglot Neural Language Models: A Case Study in Cross-Lingual Phonetic Representation Learning ... Tsvetkov, Yulia; Sitaram, Sunayana; Faruqui, Manaal. - : arXiv, 2016 BASE Show details 8 What you can cram into a single $&!#* vector: probing sentence embeddings for linguistic properties Kruszewski, German; Barrault, Loïc; Baroni, Marco. - : ACL (Association for Computational Linguistics) BASE Show details 9 Neural architectures for named entity recognition Kawakami, Kazuya; Ballesteros, Miguel; Lample, Guillaume. - : ACL (Association for Computational Linguistics) BASE Show details

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