Papers with sequence-to-sequence networks
Who wrote this book? A challenge for e-commerce (D19-55)
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| Challenge: | Modern e-commerce catalogs contain millions of references, associated with textual and visual information that is of paramount importance for the products to be found via textual or visual search. |
| Approach: | They propose a composite system that uses open data sources and deep learning components to solve this problem. |
| Outcome: | The proposed system is based on product data from Rakuten France . it is found that the top proposal has a 72% accuracy . |
Cross-Lingual Abstractive Summarization with Limited Parallel Resources (2021.acl-long)
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| Challenge: | Existing approaches to cross-lingual summarization use limited available cross-linguistic resources. |
| Approach: | They propose a multi-task framework for cross-lingual abstractive summarization that uses a single decoder to generate monolingual and cross-linguistic summaries. |
| Outcome: | Experiments on two CLS datasets show that the proposed model outperforms baseline models in low-resource and full-dataset scenarios. |
Deep JSLC: A Multimodal Corpus Collection for Data-driven Generation of Japanese Sign Language Expressions (L18-1)
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| Challenge: | Existing technologies for CG-supported data display are not able to depict all relevant features of a natural signing sequence such as facial expression, spatial references or inter-sign movement. |
| Approach: | They collected a corpus of Japanese Sign Language sentences for deep neural network learning. |
| Outcome: | The proposed model could be used to train language features in Japanese Sign Language (JSL) |