@inproceedings{chakrabarty-etal-2022-help,
title = "Help me write a Poem: Instruction Tuning as a Vehicle for Collaborative Poetry Writing",
author = "Chakrabarty, Tuhin and
Padmakumar, Vishakh and
He, He",
editor = "Goldberg, Yoav and
Kozareva, Zornitsa and
Zhang, Yue",
booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing",
month = dec,
year = "2022",
address = "Abu Dhabi, United Arab Emirates",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.emnlp-main.460",
doi = "10.18653/v1/2022.emnlp-main.460",
pages = "6848--6863",
abstract = "Recent work in training large language models (LLMs) to follow natural language instructions has opened up exciting opportunities for natural language interface design. Building on the prior success of large language models in the realm of computer assisted creativity, in this work, we present \textit{CoPoet}, a collaborative poetry writing system, with the goal of to study if LLM{'}s actually improve the quality of the generated content. In contrast to auto-completing a user{'}s text, CoPoet is controlled by user instructions that specify the attributes of the desired text, such as \textit{Write a sentence about {`}love{'}} or \textit{Write a sentence ending in {`}fly{'}}. The core component of our system is a language model fine-tuned on a diverse collection of instructions for poetry writing. Our model is not only competitive to publicly available LLMs trained on instructions (InstructGPT), but also capable of satisfying unseen compositional instructions. A study with 15 qualified crowdworkers shows that users successfully write poems with CoPoet on diverse topics ranging from \textit{Monarchy} to \textit{Climate change}, which are preferred by third-party evaluators over poems written without the system.",
}
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<abstract>Recent work in training large language models (LLMs) to follow natural language instructions has opened up exciting opportunities for natural language interface design. Building on the prior success of large language models in the realm of computer assisted creativity, in this work, we present CoPoet, a collaborative poetry writing system, with the goal of to study if LLM’s actually improve the quality of the generated content. In contrast to auto-completing a user’s text, CoPoet is controlled by user instructions that specify the attributes of the desired text, such as Write a sentence about ‘love’ or Write a sentence ending in ‘fly’. The core component of our system is a language model fine-tuned on a diverse collection of instructions for poetry writing. Our model is not only competitive to publicly available LLMs trained on instructions (InstructGPT), but also capable of satisfying unseen compositional instructions. A study with 15 qualified crowdworkers shows that users successfully write poems with CoPoet on diverse topics ranging from Monarchy to Climate change, which are preferred by third-party evaluators over poems written without the system.</abstract>
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%0 Conference Proceedings
%T Help me write a Poem: Instruction Tuning as a Vehicle for Collaborative Poetry Writing
%A Chakrabarty, Tuhin
%A Padmakumar, Vishakh
%A He, He
%Y Goldberg, Yoav
%Y Kozareva, Zornitsa
%Y Zhang, Yue
%S Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
%D 2022
%8 December
%I Association for Computational Linguistics
%C Abu Dhabi, United Arab Emirates
%F chakrabarty-etal-2022-help
%X Recent work in training large language models (LLMs) to follow natural language instructions has opened up exciting opportunities for natural language interface design. Building on the prior success of large language models in the realm of computer assisted creativity, in this work, we present CoPoet, a collaborative poetry writing system, with the goal of to study if LLM’s actually improve the quality of the generated content. In contrast to auto-completing a user’s text, CoPoet is controlled by user instructions that specify the attributes of the desired text, such as Write a sentence about ‘love’ or Write a sentence ending in ‘fly’. The core component of our system is a language model fine-tuned on a diverse collection of instructions for poetry writing. Our model is not only competitive to publicly available LLMs trained on instructions (InstructGPT), but also capable of satisfying unseen compositional instructions. A study with 15 qualified crowdworkers shows that users successfully write poems with CoPoet on diverse topics ranging from Monarchy to Climate change, which are preferred by third-party evaluators over poems written without the system.
%R 10.18653/v1/2022.emnlp-main.460
%U https://aclanthology.org/2022.emnlp-main.460
%U https://doi.org/10.18653/v1/2022.emnlp-main.460
%P 6848-6863
Markdown (Informal)
[Help me write a Poem: Instruction Tuning as a Vehicle for Collaborative Poetry Writing](https://aclanthology.org/2022.emnlp-main.460) (Chakrabarty et al., EMNLP 2022)
ACL