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Titlebook: Natural Language Processing and Chinese Computing; 13th National CCF Co Derek F. Wong,Zhongyu Wei,Muyun Yang Conference proceedings 2025 Th

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樓主: 紀(jì)念性
21#
發(fā)表于 2025-3-25 06:53:22 | 只看該作者
CouBRE: Counterfactual NLI For Low-Resource Biomedical Relation Extractiontions within a classified given text, being modeled as a classification method. There has been some recent work on converting biomedical RE to other auxiliary tasks to deal with it. However, they have all neglected the fact that this form of RE is subject to the inherent bias of the auxiliary task,
22#
發(fā)表于 2025-3-25 10:56:32 | 只看該作者
Enhancing Cross-Lingual Named Entity Recognition via?Dual Contrastive Learning Based on?MRC Frameworlow-resource languages, thus meeting the challenge of data scarcity in low-resource languages. Most of the current model-transfer methods rely on directly using multilingual models to represent text yet ignoring the cross-lingual word alignment information in multilingual models, and also neglecting
23#
發(fā)表于 2025-3-25 13:43:41 | 只看該作者
Multi-layer Sequence Labeling-Based Joint Biomedical Event Extractionxisting work has not effectively utilized trigger word information explicitly. Hence, we propose MLSL, a method based on multi-layer sequence labeling for joint biomedical event extraction. MLSL does not introduce prior knowledge and complex structures. Moreover, it explicitly incorporates the infor
24#
發(fā)表于 2025-3-25 15:48:40 | 只看該作者
EDNER: Edge Detection for?Named Entity Recognitionidespread research attention. Despite their success in many aspects, these approaches also suffer from insufficient utilization of non-entity information. In this work, we view the span-based NER task as an edge detection task and propose . (.dge .etection for .amed .ntity .ecognition). In this meth
25#
發(fā)表于 2025-3-25 20:06:02 | 只看該作者
26#
發(fā)表于 2025-3-26 01:22:37 | 只看該作者
27#
發(fā)表于 2025-3-26 06:20:24 | 只看該作者
GSEA: Global Structure-Aware Graph Neural Networks for?Entity Alignmentntegrating multi-source KGs. Existing entity alignment methods based on Graph Neural Networks mainly focus on aggregating neighborhood structure information within the original graph to generate entity embeddings. However, these methods fail to effectively leverage the global structural information
28#
發(fā)表于 2025-3-26 11:55:13 | 只看該作者
29#
發(fā)表于 2025-3-26 16:03:16 | 只看該作者
30#
發(fā)表于 2025-3-26 19:38:07 | 只看該作者
Junxiu Chen,Kehan Long,Shasha Li,Jintao Tang,Ting Wangschiede" ist aktueller denn je und macht auch vor Kliniken u.Kulturelle Unterschiede wahrnehmen und danach handeln.....Das Thema "Kulturen" ist aktueller denn je und macht auch vor Kliniken und Praxen nicht halt. Besonders bei psychischen Erkrankungen muss, schon aus biographischen Gründen, der kult
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