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Titlebook: Natural Language Processing and Chinese Computing; 12th National CCF Co Fei Liu,Nan Duan,Yu Hong Conference proceedings 2023 The Editor(s)

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樓主: Madison
21#
發(fā)表于 2025-3-25 04:52:40 | 只看該作者
A Multi-granularity Similarity Enhanced Model for?Implicit Event Argument Extractionentence-level enhancement makes the model concentrate more on effective content. Experimental results on RAMS and WikiEvents demonstrate that our proposed model can obtain state-of-the-art performance in Implicit EAE.
22#
發(fā)表于 2025-3-25 09:39:35 | 只看該作者
23#
發(fā)表于 2025-3-25 14:48:40 | 只看該作者
Dual-Prompting Interaction with?Entity Representation Enhancement for?Event Argument Extractionemployed to predict the start and end word among the input for each role. In addition, DPIERE devises position marks in event prompt template to distinguish multiple occurrences of the same argument role. Comprehensive experimental results on three benchmarks show the effectiveness of our proposed a
24#
發(fā)表于 2025-3-25 16:44:33 | 只看該作者
25#
發(fā)表于 2025-3-25 21:34:10 | 只看該作者
Coarse-to-Fine Entity Representations for?Document-Level Relation Extractionas a guidance to selectively aggregate path information between the target entity pair at a fine level. In classification, we combine the entity representations from both two levels into more comprehensive representations for relation extraction. Experimental results on two document-level RE dataset
26#
發(fā)表于 2025-3-26 04:02:56 | 只看該作者
27#
發(fā)表于 2025-3-26 05:11:17 | 只看該作者
Sheng Li,Rong Yan,Qing Wang,Juru Zeng,Xun Zhu,Yueke Liu,Henghua Li
28#
發(fā)表于 2025-3-26 08:49:26 | 只看該作者
29#
發(fā)表于 2025-3-26 14:51:12 | 只看該作者
Jing Xu,Ruifang He,Haodong Zhao,Huijie Wang,Lei Zeng
30#
發(fā)表于 2025-3-26 20:06:27 | 只看該作者
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