| Challenge: | a novel approach to generate poetry for the morphologically rich Finnish language is presented . the method is evaluated and described within the paradigm of computational creativity . |
| Approach: | They propose a method for generating poetry automatically for the morphologically rich Finnish language using a genetic algorithm. |
| Outcome: | The proposed method improves the state-of-the-art of previous Finnish poetry generators by introducing a higher degree of freedom in terms of structural creativity. |
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| Challenge: | Existing models for creative text generation are not evaluated regarding how different generated poems are from existing training sets. |
| Approach: | They evaluate the diversity of automatically generated poetry by comparing distributions of generated poetry to distributions in human poetry along structural, lexical, semantic and stylistic dimensions. |
| Outcome: | The proposed model types show that style-conditioning and character-level modeling increases diversity across virtually all dimensions. |
Automatic Poetry Generation from Prosaic Text (2020.acl-main)
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| Challenge: | In recent years, successful approaches have emerged to accurately model various aspects of natural language. |
| Approach: | They propose to combine neural networks with a poetry generation system that only uses standard text as input . they use standard text to model syntactic well-formedness and topical coherence . |
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Automatic Poetry Generation with Mutual Reinforcement Learning (D18-1)
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| Challenge: | Existing models for automatic poetry generation are based on maximum likelihood estimation (MLE) MLE-based models tend to remember common patterns of the poetry corpus, which results in loss-evaluation mismatch. |
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Acrostic Poem Generation (2020.emnlp-main)
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| Challenge: | Acrostic poems contain a hidden message; typically, the first letter of each line spells out a word or short phrase. |
| Approach: | They propose a task for acrostic poem generation in English with multiple constraints . they define the task as a generation task with multiple constraint constraints based on a conditional neural language model and a neural rhyming model . |
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Augmenting Poetry Composition with Verse by Verse (2022.naacl-industry)
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| Challenge: | a new approach to poetry generation has been developed that allows an AI to generate a full poem by itself, thus writing in a closed system. |
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Stylistic Chinese Poetry Generation via Unsupervised Style Disentanglement (D18-1)
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| Challenge: | Automatic Chinese poetry generation is one of the first attempts towards computer writing. |
| Approach: | They propose a model which requires no supervised style labeling to generate stylistic poems . they incorporate mutual information, a concept in information theory, into modeling . |
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Instruction-Guided Poetry Generation in Arabic and Its Dialects (2026.findings-acl)
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Abdelrahman Sadallah, Kareem Elozeiri, Mervat Abassy, Rania Elbadry, Mohamed Anwar, Abed Alhakim Freihat, Preslav Nakov, Fajri Koto
| Challenge: | Existing literature on Arabic poetry has focused on analysis tasks such as interpretation or metadata prediction, e.g., rhyme schemes and titles. |
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Coming to Terms: Automatic Formation of Neologisms in Hebrew (2020.findings-emnlp)
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| Challenge: | a new algorithm to generate neologisms in spoken languages relies on human creativity . a system to automatically generate a dictionary of new words is proposed . we focus on the Hebrew language due to the unusual regularity of its noun formation . |
| Approach: | They propose a system to automatically suggest new words in the Hebrew language . they focus on the Hebrew because of the unusual regularity of its noun formation . |
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Creative Natural Language Generation (2023.emnlp-tutorial)
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| Challenge: | This tutorial aims to bring awareness of the important and emerging research area of open-domain creative generation. |
| Approach: | They will review recent studies on creative language generation at sentence level as well as longer forms of text. |
| Outcome: | This paper reviews recent studies on creative language generation at sentence level as well as longer forms of text. |
Constrained Language Models for Interactive Poem Generation (2022.lrec-1)
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Andrei Popescu-Belis, Àlex Atrio, Valentin Minder, Aris Xanthos, Gabriel Luthier, Simon Mattei, Antonio Rodriguez
| Challenge: | Neural language models cannot learn constraints from data, which is scarce for a well-resourced language such as French. |
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