@inproceedings{zhang-etal-2026-plan-write,
title = "Plan{--}Write{--}Refine: An Iterative Framework for Argumentative Essay Generation",
author = "Zhang, Zhijun and
Wang, Qianlong and
Bao, Jianzhu and
Ding, Keyang and
Dai, Genan and
Zhang, Bowen and
Xu, Ruifeng and
Liang, Yongsheng",
editor = "Zhang, Yue and
Xu, Ruifeng and
Purwarianti, Ayu and
Rong, Tong and
Suzuki, Jun",
booktitle = "Findings of the {A}ssociation for {C}omputational {L}inguistics: {IJCNLP}-{AACL} 2026",
month = nov,
year = "2026",
address = "Hengqin, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.findings-aacl.74/",
pages = "1440--1460",
ISBN = "979-8-89176-444-6",
abstract = "Argumentative essay generation (AEG) aims to produce coherent and persuasive essays on controversial claims. Most existing methods follow a \textit{plan-then-write} paradigm, where a single plan is generated and used to guide long-form writing. However, the quality of the generated essay heavily depends on the initial plan, and errors or omissions in planning often propagate to the final output. To address this limitation, we propose the \textit{Plan{--}Write{--}Refine} framework, an iterative approach for AEG. It first generates an initial plan and a draft essay, then abstracts the essay to obtain condensed feedback, and refines the plan accordingly. Compared with the prior static planning methods, our framework enables iterative plan improvement and better structural organization of the essay by closing the loop between planning and writing. We conduct extensive experiments on four AEG benchmarks. Both automatic and human evaluations show that our framework achieves consistent improvements over strong baselines."
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<abstract>Argumentative essay generation (AEG) aims to produce coherent and persuasive essays on controversial claims. Most existing methods follow a plan-then-write paradigm, where a single plan is generated and used to guide long-form writing. However, the quality of the generated essay heavily depends on the initial plan, and errors or omissions in planning often propagate to the final output. To address this limitation, we propose the Plan–Write–Refine framework, an iterative approach for AEG. It first generates an initial plan and a draft essay, then abstracts the essay to obtain condensed feedback, and refines the plan accordingly. Compared with the prior static planning methods, our framework enables iterative plan improvement and better structural organization of the essay by closing the loop between planning and writing. We conduct extensive experiments on four AEG benchmarks. Both automatic and human evaluations show that our framework achieves consistent improvements over strong baselines.</abstract>
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%0 Conference Proceedings
%T Plan–Write–Refine: An Iterative Framework for Argumentative Essay Generation
%A Zhang, Zhijun
%A Wang, Qianlong
%A Bao, Jianzhu
%A Ding, Keyang
%A Dai, Genan
%A Zhang, Bowen
%A Xu, Ruifeng
%A Liang, Yongsheng
%Y Zhang, Yue
%Y Xu, Ruifeng
%Y Purwarianti, Ayu
%Y Rong, Tong
%Y Suzuki, Jun
%S Findings of the Association for Computational Linguistics: IJCNLP-AACL 2026
%D 2026
%8 November
%I Association for Computational Linguistics
%C Hengqin, China
%@ 979-8-89176-444-6
%F zhang-etal-2026-plan-write
%X Argumentative essay generation (AEG) aims to produce coherent and persuasive essays on controversial claims. Most existing methods follow a plan-then-write paradigm, where a single plan is generated and used to guide long-form writing. However, the quality of the generated essay heavily depends on the initial plan, and errors or omissions in planning often propagate to the final output. To address this limitation, we propose the Plan–Write–Refine framework, an iterative approach for AEG. It first generates an initial plan and a draft essay, then abstracts the essay to obtain condensed feedback, and refines the plan accordingly. Compared with the prior static planning methods, our framework enables iterative plan improvement and better structural organization of the essay by closing the loop between planning and writing. We conduct extensive experiments on four AEG benchmarks. Both automatic and human evaluations show that our framework achieves consistent improvements over strong baselines.
%U https://aclanthology.org/2026.findings-aacl.74/
%P 1440-1460
Markdown (Informal)
[Plan–Write–Refine: An Iterative Framework for Argumentative Essay Generation](https://aclanthology.org/2026.findings-aacl.74/) (Zhang et al., Findings 2026)
ACL
- Zhijun Zhang, Qianlong Wang, Jianzhu Bao, Keyang Ding, Genan Dai, Bowen Zhang, Ruifeng Xu, and Yongsheng Liang. 2026. Plan–Write–Refine: An Iterative Framework for Argumentative Essay Generation. In Findings of the Association for Computational Linguistics: IJCNLP-AACL 2026, pages 1440–1460, Hengqin, China. Association for Computational Linguistics.