English(EN) A BART-based approach with hierarchical strategy for Vietnamese abstractive multi-document summarization

新的BART策略增强了越南语多文档摘要能力

作者 PulseAugur 编辑部 · [2 个来源] · 2026-06-17 20:46

研究人员开发了一种新的分层策略，使用BART模型来改进越南语文本的抽取式多文档摘要。该方法在聚合和总结文档之前先对单个文档进行精简，并采用一种新颖的方法，利用黄金摘要来指导文档缩短。该技术在VLSP 2022测试集上取得了0.2468的ROUGE2-F1分数，并已向社区提供了额外的训练数据。 AI

影响这项研究为低资源语言的抽取式摘要提供了一种新颖的方法，有望改善信息获取。

排序理由该集群包含一篇详细介绍特定NLP任务新方法的学术论文。

AI 生成摘要 · Google Gemini · 来自 2 个来源。我们如何撰写摘要 →

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arXiv cs.AI TIER_1 English(EN) · Vu Nguyen Nguyen Xuan, Huy Ngo Quang · 2026-06-19 04:00

一种基于BART的具有分层策略的越南语抽象多文档摘要方法

arXiv:2606.19591v1 Announce Type: cross Abstract: In this technical report, we focus on solving the challenge of Vietnamese multi-document abstractive summarization, introduced in the International Workshop on Vietnamese Language and Speech Processing (VLSP) 2022. We choose to fo…
arXiv cs.CL TIER_1 English(EN) · Huy Ngo Quang · 2026-06-17 20:46

一种基于BART的分层策略的越南语抽象式多文档摘要方法

In this technical report, we focus on solving the challenge of Vietnamese multi-document abstractive summarization, introduced in the International Workshop on Vietnamese Language and Speech Processing (VLSP) 2022. We choose to follow the popular hierarchical approach, i.e. conde…