QASE Enhanced PLMs: Improved Control in Text Generation for MRC
<|reference_start|>QASE Enhanced PLMs: Improved Control in Text Generation for MRC: 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.<|reference_end|>
@article{ai2024qase,
    title={QASE Enhanced PLMs: Improved Control in Text Generation for MRC},
    author={Lin Ai, Zheng Hui, Zizhou Liu, Julia Hirschberg},
    journal={arXiv preprint arXiv:2403.04771},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.04771},
    primaryClass={cs.CL}
}