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Homepage2Vec: Language-Agnostic Website Embedding and Classification ...
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2
Better than Average: Paired Evaluation of NLP systems ...
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3
Classifying Dyads for Militarized Conflict Analysis ...
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4
Classifying Dyads for Militarized Conflict Analysis
In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2021)
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5
Cognitive Network Topology and Optimization of the Mental Lexicon ...
Burlacu, Adrian; West, Robert. - : Unpublished, 2021
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6
Linguistic effects on news headline success: Evidence from thousands of online field experiments (Registered Report Protocol)
In: PLoS One (2021)
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7
On the Limitations of Cross-lingual Encoders as Exposed by Reference-Free Machine Translation Evaluation ...
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8
On the limitations of cross-lingual encoders as exposed by reference-free machine translation evaluation
Zhao, Wei; Glavaš, Goran; Peyrard, Maxime. - : Association for Computational Linguistics, 2020
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9
Robust Cross-lingual Embeddings from Parallel Sentences ...
Abstract: Recent advances in cross-lingual word embeddings have primarily relied on mapping-based methods, which project pretrained word embeddings from different languages into a shared space through a linear transformation. However, these approaches assume word embedding spaces are isomorphic between different languages, which has been shown not to hold in practice (Søgaard et al., 2018), and fundamentally limits their performance. This motivates investigating joint learning methods which can overcome this impediment, by simultaneously learning embeddings across languages via a cross-lingual term in the training objective. We propose a bilingual extension of the CBOW method which leverages sentence-aligned corpora to obtain robust cross-lingual word and sentence representations. Our approach significantly improves cross-lingual sentence retrieval performance over all other approaches while maintaining parity with the current state-of-the-art methods on word-translation. It also achieves parity with a deep RNN method ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences; Information Retrieval cs.IR; Machine Learning cs.LG
URL: https://dx.doi.org/10.48550/arxiv.1912.12481
https://arxiv.org/abs/1912.12481
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10
Crosslingual Document Embedding as Reduced-Rank Ridge Regression ...
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11
Why the World Reads Wikipedia ...
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12
Why the World Reads Wikipedia ...
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13
Why the World Reads Wikipedia ...
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14
Causal Effects of Brevity on Style and Success in Social Media ...
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15
Message Distortion in Information Cascades
In: http://infoscience.epfl.ch/record/270657 (2019)
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16
Message Distortion in Information Cascades ...
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17
Reverse-Engineering Satire, or "Paper on Computational Humor Accepted despite Making Serious Advances"
In: http://infoscience.epfl.ch/record/271147 (2019)
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18
Why the World Reads Wikipedia: Beyond English Speakers
In: http://infoscience.epfl.ch/record/270302 (2019)
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19
Crosslingual Document Embedding as Reduced-Rank Ridge Regression
In: http://infoscience.epfl.ch/record/263893 (2019)
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20
Churn Intent Detection in Multilingual Chatbot Conversations and Social Media ...
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