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Titlebook: Neural Information Processing; 30th International C Biao Luo,Long Cheng,Chaojie Li Conference proceedings 2024 The Editor(s) (if applicable

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Shuyu Jiang,Dengbiao Tu,Xingshu Chen,Rui Tang,Wenxian Wang,Haizhou Wang
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Improve Conversational Search with Multi-document Informationng data for extracting multiple document information. We further present the Passage-Segment-Document (PSD) post-training method to train the reranker using the extracted multi-document information in combination with a multi-task learning method. The results on the MultiDoc2Dial dataset verifies th
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Recurrent Update Representation Based on Multi-head Attention Mechanism for Joint Entity and Relatiooach we are able to leverage the relationship information between entities for relational triple extraction. Our experimental results on four public datasets show that our approach is effective and the model outperforms all baseline models.
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Decoupling Style from Contents for Positive Text Reframingunes the model for the input sequence with two special symbols to decouple style from the contents. We apply contrastive learning to enhance the model that learns a more robust contextual representation. The experimental results on the PPF dataset, show that our approach outperforms baselines by fin
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