Zobrazeno 1 - 10
of 5 710
pro vyhledávání: '"Abstractive summarization"'
Abstractive summarization has made significant strides in condensing and rephrasing large volumes of text into coherent summaries. However, summarizing administrative documents presents unique challenges due to domain-specific terminology, OCR-genera
Externí odkaz:
http://arxiv.org/abs/2412.08196
Autor:
Zhang, Zhejun1 (AUTHOR), Guo, Shaoting1 (AUTHOR), Zhou, Wenqing1 (AUTHOR), Luo, Yingying1 (AUTHOR), Zhu, Yingqi1 (AUTHOR), Zhang, Lin1,2 (AUTHOR), Li, Lei1 (AUTHOR) leili@bupt.edu.cn
Publikováno v:
Scientific Reports. 1/2/2025, Vol. 15 Issue 1, p1-19. 19p.
India's vast linguistic diversity presents unique challenges and opportunities for technological advancement, especially in the realm of Natural Language Processing (NLP). While there has been significant progress in NLP applications for widely spoke
Externí odkaz:
http://arxiv.org/abs/2412.18163
Language models (LMs) have shown outstanding performance in text summarization including sensitive domains such as medicine and law. In these settings, it is important that personally identifying information (PII) included in the source document shou
Externí odkaz:
http://arxiv.org/abs/2412.12040
Autor:
Dhakal, Prakash, Baral, Daya Sagar
Automatic text summarization in Nepali language is an unexplored area in natural language processing (NLP). Although considerable research has been dedicated to extractive summarization, the area of abstractive summarization, especially for low-resou
Externí odkaz:
http://arxiv.org/abs/2409.19566
Extract-then-Abstract is a naturally coherent paradigm to conduct abstractive summarization with the help of salient information identified by the extractive model. Previous works that adopt this paradigm train the extractor and abstractor separately
Externí odkaz:
http://arxiv.org/abs/2409.11827
Autor:
Nagar, Aishik, Liu, Yutong, Liu, Andy T., Schlegel, Viktor, Dwivedi, Vijay Prakash, Kaliya-Perumal, Arun-Kumar, Kalanchiam, Guna Pratheep, Tang, Yili, Tan, Robby T.
Medical abstractive summarization faces the challenge of balancing faithfulness and informativeness. Current methods often sacrifice key information for faithfulness or introduce confabulations when prioritizing informativeness. While recent advancem
Externí odkaz:
http://arxiv.org/abs/2408.12095
In abstractive summarization, the challenge of producing concise and accurate summaries arises from the vast amount of information contained in the source document. Consequently, although Large Language Models (LLMs) can generate fluent text, they of
Externí odkaz:
http://arxiv.org/abs/2409.18618
Autor:
Saxena, Rohit, Keller, Frank
Movie screenplay summarization is challenging, as it requires an understanding of long input contexts and various elements unique to movies. Large language models have shown significant advancements in document summarization, but they often struggle
Externí odkaz:
http://arxiv.org/abs/2408.06281