BIPro: Zero-shot Chinese Poem Generation via Block Inverse Prompting Constrained Generation Framework
Xu Zou

TL;DR
This paper introduces BIPro, a novel zero-shot Chinese poem generation framework that uses block inverse prompting to significantly enhance the quality of constrained poem generation with less powerful models, outperforming state-of-the-art systems.
Contribution
The paper proposes the BIPro framework with two block inverse prompting methods, revise and rewrite, to improve zero-shot constrained poem generation without additional training.
Findings
BIPro outperforms GPT-4 and domain-specific systems in human evaluations.
Poems generated by BIPro are closer to human literary quality.
The approach narrows the gap between AI and human poetry in constrained tasks.
Abstract
Recently, generative pre-trained models have made significant strides, particularly highlighted by the release of ChatGPT and GPT-4, which exhibit superior cross-domain capabilities. However, these models still face challenges on constrained writing tasks like poem generation under open-domain titles. In response to this challenge, we introduce Block Inverse Prompting (BIPro) constrained generation framework. BIPro leverages two block inverse prompting methods, revise and rewrite, that mimic the process of human text writing using block generative models. It significantly improves the zero-shot generation quality on the formidable constrained generation task of open-domain traditional-form Chinese poem generation. Based on a less powerful block generative model GLM-10B-Chinese, poems composed via BIPro without priming or additional training outperform both most advanced direct…
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Taxonomy
TopicsNatural Language Processing Techniques · Topic Modeling · Advanced Text Analysis Techniques
MethodsAttention Is All You Need · Dense Connections · Label Smoothing · Layer Normalization · Dropout · Adam · Residual Connection · Byte Pair Encoding · Linear Layer · Softmax
