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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 – 7 of 7 1 Leveraging Adversarial Training in Self-Learning for Cross-Lingual Text Classification ... Dong, Xin; Zhu, Yaxin; Zhang, Yupeng. - : arXiv, 2020 BASE Show details 2 Contrastive Visual-Linguistic Pretraining ... Shi, Lei; Shuang, Kai; Geng, Shijie. - : arXiv, 2020 BASE Show details 3 Incorporating Pragmatic Reasoning Communication into Emergent Language ... Kang, Yipeng; Wang, Tonghan; de Melo, Gerard. - : arXiv, 2020 BASE Show details 4 Sentence Analogies: Exploring Linguistic Relationships and Regularities in Sentence Embeddings ... Zhu, Xunjie; de Melo, Gerard. - : arXiv, 2020 BASE Show details 5 Sentence Analogies: Linguistic Regularities in Sentence Embeddings ... The 28th International Conference on Computational Linguistics 2020; de Melo, Gerard; Zhu, Xunjie. - : Underline Science Inc., 2020 BASE Show details 6 1055 - Domain-Specific Sentiment Lexicons Induced from Labeled Documents ... The 28th International Conference on Computational Linguistics 2020; de Melo, Gerard; Dong, Xin. - : Underline Science Inc., 2020 BASE Show details 7 Cross-Lingual Emotion Lexicon Induction using Representation Alignment in Low-Resource Settings ... The 28th International Conference on Computational Linguistics 2020; de Melo, Gerard; Ramachandran, Arun. - : Underline Science Inc., 2020 Abstract: Emotion lexicons provide information about associations between words and emotions. They have proven useful in analyses of reviews, literary texts, and posts on social media, among other things. We evaluate the feasibility of deriving emotion lexicons cross-lingually for over 350 languages, many of them resource-poor, from existing emotion lexicons in resource-rich languages. For this, we start out from very small corpora to induce cross-lingually aligned vector spaces. Our study empirically analyses the effectiveness of the induced emotion lexicons by measuring translation precision and correlations with existing emotion lexicons, along with measurements on a downstream task of sentence emotion prediction. ... Keyword: Computer and Information Science; Natural Language Processing; Neural Network URL: https://dx.doi.org/10.48448/mype-fj14 https://underline.io/lecture/6292-cross-lingual-emotion-lexicon-induction-using-representation-alignment-in-low-resource-settings BASE Hide details

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