{"slug": "transformer-models-for-text-summarization-a-comparative-study-of-bart-bert-and", "title": "Transformer Models for Text Summarization: A Comparative Study of BART, BERT, and RoBERTa", "summary": "A study submitted to arXiv on 2 Jun 2026 compares transformer models BERT, RoBERTa, and BART for text summarization, examining their architectures, pretraining strategies, and suitability for extractive and abstractive tasks. The review highlights the rapid development of automatic text summarization driven by advancements in natural language processing.", "body_md": "# Computer Science > Computation and Language\n\n[Submitted on 2 Jun 2026]\n\n# Title:Transformer Models for Text Summarization: A Comparative Study of BART, BERT, and RoBERTa\n\n[View PDF](/pdf/2608.19200)\n\nAbstract:Text summarization refers to the task of condensing a document into a shorter version while preserving its key information. Automatic text summarization (ATS), driven by advancements in natural language processing (NLP), has developed rapidly in recent years. ATS methods are commonly categorized by input type (such as single-document or multi-document summarization) and by output type (extractive, abstractive, and hybrid). This article presents a focused review of modern summarization techniques with an emphasis on transformer based models and large language models (LLMs), specifically BERT, RoBERTa and BART. It examines their architectures, pretraining strategies, and their suitability for extractive and abstractive summarization tasks.\n\n### References & Citations\n\nLoading...\n\n# Bibliographic and Citation Tools\n\nBibliographic Explorer\n\n*(*[What is the Explorer?](https://info.arxiv.org/labs/showcase.html#arxiv-bibliographic-explorer))\nConnected Papers\n\n*(*[What is Connected Papers?](https://www.connectedpapers.com/about))\nLitmaps\n\n*(*[What is Litmaps?](https://www.litmaps.co/))\nscite Smart Citations\n\n*(*[What are Smart Citations?](https://www.scite.ai/))# Code, Data and Media Associated with this Article\n\nalphaXiv\n\n*(*[What is alphaXiv?](https://alphaxiv.org/))\nCatalyzeX Code Finder for Papers\n\n*(*[What is CatalyzeX?](https://www.catalyzex.com))\nDagsHub\n\n*(*[What is DagsHub?](https://dagshub.com/))\nGotit.pub\n\n*(*[What is GotitPub?](http://gotit.pub/faq))\nHugging Face\n\n*(*[What is Huggingface?](https://huggingface.co/huggingface))\nScienceCast\n\n*(*[What is ScienceCast?](https://sciencecast.org/welcome))# Demos\n\n# Recommenders and Search Tools\n\nInfluence Flower\n\n*(*[What are Influence Flowers?](https://influencemap.cmlab.dev/))\nCORE Recommender\n\n*(*[What is CORE?](https://core.ac.uk/services/recommender))# arXivLabs: experimental projects with community collaborators\n\narXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.\n\nBoth individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.\n\nHave an idea for a project that will add value for arXiv's community? [ Learn more about arXivLabs](https://info.arxiv.org/labs/index.html).", "url": "https://wpnews.pro/news/transformer-models-for-text-summarization-a-comparative-study-of-bart-bert-and", "canonical_source": "https://arxiv.org/abs/2608.19200", "published_at": "2026-08-21 04:00:00+00:00", "updated_at": "2026-08-21 04:13:11.166620+00:00", "lang": "en", "topics": ["natural-language-processing", "large-language-models", "machine-learning"], "entities": ["arXiv", "BERT", "RoBERTa", "BART"], "alternates": {"html": "https://wpnews.pro/news/transformer-models-for-text-summarization-a-comparative-study-of-bart-bert-and", "markdown": "https://wpnews.pro/news/transformer-models-for-text-summarization-a-comparative-study-of-bart-bert-and.md", "text": "https://wpnews.pro/news/transformer-models-for-text-summarization-a-comparative-study-of-bart-bert-and.txt", "jsonld": "https://wpnews.pro/news/transformer-models-for-text-summarization-a-comparative-study-of-bart-bert-and.jsonld"}}