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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 – 4 of 4 1 Definition Modelling for Appropriate Specificity ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Arase, Yuki; Huang, Han. - : Underline Science Inc., 2021 BASE Show details 2 Distinct Label Representations for Few-Shot Text Classification ... 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; Arase, Yuki; Kajiwara, Tomoyuki. - : Underline Science Inc., 2021 BASE Show details 3 Language-agnostic Representation from Multilingual Sentence Encoders for Cross-lingual Similarity Estimation ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Arase, Yuki; Kajiwara, Tomoyuki; Onizuka, Makoto; Tiyajamorn, Nattapong. - : Underline Science Inc., 2021 Abstract: Anthology paper link: https://aclanthology.org/2021.emnlp-main.612/ Abstract: We propose a method to distil language-agnostic meaning embedding using a multilingual sentence encoder. By removing language-specific information from the original embedding, we retrieve an embedding that fully represents the meaning of the sentence. The proposed method relies only on parallel corpora without any human annotations. Our meaning embedding allows for efficient cross-lingual sentence similarity estimation using a simple cosine similarity calculation. Experimental results of both the quality estimation of machine translation and cross-lingual semantic textual similarity tasks reveal that our method consistently outperforms the strong baselines using the original multilingual embeddings. The method also consistently improves the performance of any pre-trained multilingual sentence encoder, even in low-resource language pairs, where only tens of thousands of parallel sentence pairs are available. ... Keyword: Computational Linguistics; Machine Learning; Machine Learning and Data Mining; Natural Language Processing URL: https://underline.io/lecture/37510-language-agnostic-representation-from-multilingual-sentence-encoders-for-cross-lingual-similarity-estimation https://dx.doi.org/10.48448/9fqx-z240 BASE Hide details 4 Distilling Word Meaning in Context from Pre-trained Language Models ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Arase, Yuki; Arase, Yuki. - : Underline Science Inc., 2021 BASE Show details

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