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GPT-based Generation for Classical Chinese Poetry
We present a simple yet effective method for generating high qual- ity classical Chinese poetry with Generative Pre-trained Language Model (GPT)[5]. The method adopts a simple GPT model, without using any human crafted rules or features, or designing any additional neural compo- nents. While the proposed model learns to generate various forms of clas- sical Chinese poems, including Jueju(绝句), Lu ̈shi(律诗), various Cipai(词牌) and Couples(对联), the generated poems are of very high quality. We also propose and implement a method to fine-tune the model to generate acrostic poetry. To the best of our knowledge, this is the first to em- ploy GPT in developing a poetry generation system. We have released an online mini demonstration program on Wechat1 to show the generation capability of the proposed method for classical Chinese poetry.
Jill Walker Rettberg - 18.09.2019 - 11:08
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ReRites - Raw Output / Responses (paperback)
ReRites is a project consisting of 12 poetry books (generated by a computer then edited by poet David Jhave Johnston) created between May 2017-18. Jhave produced one book of poetry per month, utilizing neural networks trained on a contemporary poetry corpus to generate source texts which were then edited into the ReRites poems. (The limited edition boxset) is a conceptual proof-of-concept about the impact of augmented creativity and human-machine symbiosis.
This book contains 60 pages of poems selected from the over 4500 pages of ReRites poems; some of the Raw Output generated by the computer; and 8 Response essays.
Introduced & edited by Stephanie Strickland with essays by Allison Parrish, Johanna Drucker, Kyle Booten, John Cayley, Lai-Tze Fan, Nick Montfort, Mairéad Byrne, Chris Funkhouser, and an author-note from David (Jhave) Johnston.
David Jhave Johnston - 25.05.2021 - 19:20
