QASE Enhanced PLMs: Improved Control in Text Generation for MRC

• URL: http://arxiv.org/abs/2403.04771v1
• Date: Mon, 26 Feb 2024 05:34:16 GMT
• Title: QASE Enhanced PLMs: Improved Control in Text Generation for MRC
• Authors: Lin Ai, Zheng Hui, Zizhou Liu, Julia Hirschberg,
• Abstract summary: We introduce the Question-Attended Span Extraction (QASE) module to address the challenges of out-of-control generation in generative models for machine reading comprehension. integrated during the fine-tuning of pre-trained generative language models (PLMs), QASE enables these PLMs to match SOTA extractive methods.
• Score: 6.602323571343169
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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