QASE Enhanced PLMs: Improved Control in Text Generation for MRC

arXiv:2403.04771v1 Announce Type: new
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.

abstract arxiv challenges control cs.cl extraction fine-tuning generative generative models language language models machine match question reading sota text text generation type