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1. Story Generation

   In the field of artificial intelligence (AI) the automated generation of stories has been a subject of research for over fifty years. The underlying concept of "story" in story generation research is functional and does not imply any aesthetic notion. This is important because the evaluation of generated stories does not necessarily use the criterion of a readable and appealing text. Research on storytelling systems (computational systems capable of telling a story) initially arose as a part of the general trend in AI to build computational solutions that could undertake tasks that are easy for humans and difficult for machines. Some such efforts, such as computer vision and speech processing, have achieved success and given rise to commercial applications, whereas others, such as natural language understanding and story generation, still remain at the exploratory research stage.

   (Source: Author's introduction)

   Thor Baukhol Madsen - 05.02.2015 - 11:11

2. 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