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Found 6 papers, 4 papers with code
Meta Ensemble for Japanese-Chinese Neural Machine Translation: Kyoto-U+ECNU Participation to WAT 2020
This paper describes the Japanese-Chinese Neural Machine Translation (NMT) system submitted by the joint team of Kyoto University and East China Normal University (Kyoto-U+ECNU) to WAT 2020 (Nakazawa et al., 2020).
Self-Supervised Interest Transfer Network via Prototypical Contrastive Learning for Recommendation
In this paper, we propose a cross-domain recommendation method: Self-supervised Interest Transfer Network (SITN), which can effectively transfer invariant knowledge between domains via prototypical contrastive learning.
Textual Enhanced Contrastive Learning for Solving Math Word Problems
Solving math word problems is the task that analyses the relation of quantities and requires an accurate understanding of contextual natural language information.
Seeking Diverse Reasoning Logic: Controlled Equation Expression Generation for Solving Math Word Problems
To solve Math Word Problems, human students leverage diverse reasoning logic that reaches different possible equation solutions.
MOEF: Modeling Occasion Evolution in Frequency Domain for Promotion-Aware Click-Through Rate Prediction
In this paper, we propose a novel CTR model named MOEF for recommendations under frequent changes of occasions.
Solving Math Word Problems with Multi-Encoders and Multi-Decoders
Math word problems solving remains a challenging task where potential semantic and mathematical logic need to be mined from natural language.
