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arXiv · 2410.15687

DomainSum: A Hierarchical Benchmark for Fine-Grained Domain Shift in Abstractive Text Summarization

Haohan Yuan·Haopeng Zhang
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Abstract

Most research on abstractive summarization focuses on single-domain applications, often neglecting how domain shifts between documents affect performance and the generalization ability of summarization models. To address this issue, we introduce DomainSum, a hierarchical benchmark designed to capture fine-grained domain shifts in abstractive summarization. We categorize these shifts into three levels: genre, style, and topic, and demonstrate through comprehensive benchmark analysis that they follow a hierarchical structure. Furthermore, we evaluate the domain generalization capabilities of commonly used pre-trained language models (PLMs) and large language models (LLMs) in in-domain and cross-domain settings.

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Haohan Yuan, Haopeng Zhang. 2024-10-21. DomainSum: A Hierarchical Benchmark for Fine-Grained Domain Shift in Abstractive Text Summarization. https://arxiv.org/abs/2410.15687

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