Logic: Long-form Outline Generation via Imitative and Critical Self-refinement

Challenge:	Existing methods for long-form outline generation have low knowledge density and lack detail . retrieval-augmented approaches struggle to maintain logical coherence across retrieved information .
Approach:	They propose a system that mimics human writers' refinement process by mimicking outlines through imitation and critical self-refinement.
Outcome:	The proposed system improves on the FreshWiki and WikiOutline datasets and establishes a coherent planning framework and structured knowledge base.

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Overview

Challenge

Approach

Outcome

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Hengwei Liu, Haoyuan Ma, Qingqing Lyu, Daoxin Zhang, Yao Hu, Yongliang Shen, Yin Zhang, Weiming Lu

Challenge:	Logic-RL is a framework that transforms critique-guided outline refinement into a learnable policy through reinforcement learning.
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Summarize, Outline, and Elaborate: Long-Text Generation via Hierarchical Supervision from Extractive Summaries (2022.coling-1)

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Xiaofei Sun, Zijun Sun, Yuxian Meng, Jiwei Li, Chun Fan

Text Generation

Challenge:	Existing models focus on local word prediction, and cannot make high level plans on what to generate.
Approach:	They propose a pipelined system that summarises, outlines and elaborates on each bullet point to generate the corresponding segment.
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Arg-LLaDA: Argument Summarization via Large Language Diffusion Models and Sufficiency-Aware Refinement (2026.acl-long)

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Hao Li, Yizheng Sun, Viktor Schlegel, Kailai Yang, Riza Batista-Navarro, Goran Nenadic

Text Generation

Challenge:	Existing approaches to argument summarization rely on single-pass generation, offering limited support for factual correction or structural refinement.
Approach:	They propose a large language diffusion framework that iteratively improves argument summarization by sufficiency-guided remasking and regeneration.
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RAPID: Efficient Retrieval-Augmented Long Text Generation with Writing Planning and Information Discovery (2025.findings-acl)

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Hongchao Gu, Dexun Li, Kuicai Dong, Hao Zhang, Hang Lv, Hao Wang, Defu Lian, Yong Liu, Enhong Chen

Responsible & Trustworthy NLP

Challenge:	Existing methods for knowledge-intensive long texts struggle with issues like hallucinations, topic incoherence, and significant latency.
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Boundary Matters: Leveraging Structured Text Plots for Long Text Outline Generation (2025.findings-emnlp)

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Yuanchi Ma, Jiamou Liu, Hui He, Libo Zhang, Haoyuan Li, Zhendong Niu

Challenge:	Existing methods for generating readable outlines are inability to segment long texts .
Approach:	They propose an unsupervised framework to guide large language model outline generation . framework ensures each structured plot encapsulates complete causality by accurately identifying plot boundaries.
Outcome:	The proposed framework ensures that each structured plot encapsulates complete causality by accurately identifying plot boundaries.

Advancing Topic Segmentation and Outline Generation in Chinese Texts: The Paragraph-level Topic Representation, Corpus, and Benchmark (2024.lrec-main)

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Feng Jiang, Weihao Liu, Xiaomin Chu, Peifeng Li, Qiaoming Zhu, Haizhou Li

Semantic Text Processing

Challenge:	Compared with sentence-level topic structure, paragraph-level topics can grasp and understand the context of a document from a higher level.
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Outcome:	The proposed method achieves the largest Chinese paragraph-level topic structure corpus, achieving high quality.

RSTGen: Imbuing Fine-Grained Interpretable Control into Long-FormText Generators (2022.naacl-main)

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Rilwan Adewoyin, Ritabrata Dutta, Yulan He

Explainability & Interpretability in NLP

Challenge:	Using a framework based on Rhetorical Structure Theory, we aim to improve the cohesion and coherence of long-form text generated by language models.
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DOC: Improving Long Story Coherence With Detailed Outline Control (2023.acl-long)

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Kevin Yang, Dan Klein, Nanyun Peng, Yuandong Tian

Challenge:	Detailed Outline Control (DOC) framework improves long-range plot coherence . human evaluations of DOC show it outperforms strong Re3 on plot cohesion, outline relevance and interestingness .
Approach:	They propose a Detailed Outline Control framework to improve long-range plot coherence . the detailed outliner creates a more detailed, hierarchically structured outline . they propose doc with a detailed controller to ensure the more detailed outline is respected .
Outcome:	The proposed framework outperforms Re3 on plot coherence, outline relevance and interestingness.

Logic2Text: High-Fidelity Natural Language Generation from Logical Forms (2020.findings-emnlp)

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Zhiyu Chen, Wenhu Chen, Hanwen Zha, Xiyou Zhou, Yunkai Zhang, Sairam Sundaresan, William Yang Wang

Multimodality

Challenge:	Recent studies on Natural Language Generation (NLG) from structured data focus on surface descriptions of simple record sequences, for example, attribute-value pairs of fixed or very limited schema.
Approach:	They propose to use a large-scale dataset to generate NLG from logical forms to obtain controllable and faithful generations from structured data.
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Decomposing Argumentative Essay Generation via Dialectical Planning of Complex Reasoning (2024.findings-acl)

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Yuhang He, Jianzhu Bao, Yang Sun, Bin Liang, Min Yang, Bing Qin, Ruifeng Xu

Reasoning

Challenge:	Argumentative Essay Generation (AEG) is a challenging task in computational argumentation, where detailed logical reasoning and effective rhetorical skills are essential.
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