Abstract
Large Language Models work quite well with general-purpose data and many tasks in Natural Language Processing. However, they show several limitations when used for a task such as domain-specific abstractive text summarization. This paper identifies three of those limitations as research problems in the context of abstractive text summarization: 1) Quadratic complexity of transformer-based models with respect to the input text length; 2) Model Hallucination, which is a model’s ability to generate factually incorrect text; and 3) Domain Shift, which happens when the distribution of the model’s training and test corpus is not the same. Along with a discussion of the open research questions, this paper also provides an assessment of existing state-of-the-art techniques relevant to domain-specific text summarization to address the research gaps.
| Original language | English |
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| Title of host publication | Proceedings of the 15th International Conference on Agents and Artificial Intelligence - (Volume 3) |
| Editors | Ana Paula Rocha, Luc Steels, Jaap van den Herik |
| Publisher | SCITEPRESS |
| Pages | 682-689 |
| Number of pages | 7 |
| ISBN (Print) | 978-989-758-623-1 |
| DOIs | |
| Publication status | Published - 2023 |
| Event | 15th International Conference on Agents and Artificial Intelligence, ICAART 2023 - Lisbon, Portugal Duration: 22 Feb 2023 → 24 Feb 2023 Conference number: 15 https://icaart.scitevents.org |
Publication series
| Name | Proceedings International Conference on Agents and Artificial Intelligence )ICAART) |
|---|---|
| Publisher | SciTePress |
| Number | 15 |
| Volume | 2023 |
| ISSN (Print) | 2184-433X |
Conference
| Conference | 15th International Conference on Agents and Artificial Intelligence, ICAART 2023 |
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| Country/Territory | Portugal |
| City | Lisbon |
| Period | 22/02/23 → 24/02/23 |
| Other | The purpose of the International Conference on Agents and Artificial Intelligence is to bring together researchers, engineers and practitioners interested in the theory and applications in the areas of Agents and Artificial Intelligence. Two simultaneous related tracks will be held, covering both applications and current research work. One track focuses on Agents, Multi-Agent Systems and Software Platforms, Distributed Problem Solving and Distributed AI in general. The other track focuses mainly on Artificial Intelligence, Knowledge Representation, Planning, Learning, Scheduling, Perception Reactive AI Systems, and Evolutionary Computing and other topics related to Intelligent Systems and Computational Intelligence. |
| Internet address |