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QASE Enhanced PLMs: Improved Control in Text Generation for MRC

arXiv 2403.04771 ↗First posted 26 Feb 2024cs.CLcited by 0

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Abstract (arXiv)

To address the challenges of out-of-control generation in generative models for machine reading comprehension (MRC), we introduce the Question-Attended Span Extraction (QASE) module. Integrated during the fine-tuning of pre-trained generative language models (PLMs), QASE enables these PLMs to match SOTA extractive methods and outperform leading LLMs like GPT-4 in MRC tasks, without significant increases in computational costs.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 29 of its 38 references that are in the map. First posted on arXiv 26 Feb 2024.

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References · 29

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17 more
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