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Pimbblet, Kevin , Moreland, Sam , OKPARA, GODSPOWER ·

YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.5281/zenodo.17822780

This study enhances text summarization techniques using advanced transformer models to handle complex documents like those in the BIGPATENT dataset, which includes 1.3 million U.S. patent documents. We focused on integrating self-attention mechanisms and coreference resolution to improve summary quality. Four models—LED, DistilBART, BigBird-Pegasus, and LongT5—were fine-tuned and evaluated using ROUGE, BLEU, and METEOR metrics. The results showed significant performance gains, with LED achieving a ROUGE-1 score of 95.38% and DistilBART achieving 91.94% on BLEU, marking a 50% improvement over previous studies. These findings confirm the effectiveness of our methodologies and emphasize the importance of high computational resources. Future work could explore multi-lingual and multi-modal data and develop user-friendly interfaces to broaden the models’ applicability.

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Computer Science

Artificial Intelligence

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Automatic summarization Computer science Coreference Artificial intelligence Natural language processing Transformer Information retrieval Bridging (networking) Data science Headline Machine learning Data mining Data modeling F1 score

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Type: dissertation
Landing Page: https://doi.org/10.5281/zenodo.17822780
OA Status: green
OpenAlex ID: https://openalex.org/W7110925557

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OpenAlex ID: https://openalex.org/W7110925557

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DOI: https://doi.org/10.5281/zenodo.17822780

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Title: Long-Text Summarisation

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Type: dissertation

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Publication year: 2025

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Publication date: 2025-12-04

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Authors: Pimbblet, Kevin, Moreland, Sam, OKPARA, GODSPOWER

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Landing page: https://doi.org/10.5281/zenodo.17822780

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OA status: green

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OA URL: https://doi.org/10.5281/zenodo.17822780

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Concepts: Automatic summarization, Computer science, Coreference, Artificial intelligence, Natural language processing, Transformer, Information retrieval, Bridging (networking), Data science, Headline, Machine learning, Data mining, Data modeling, F1 score

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