Plan Dynamically, Express Rhetorically: A Debate-Driven Rhetorical Framework for Argumentative Writing
Xueguan Zhao, Wenpeng Lu, Chaoqun Zheng, Weiyu Zhang, Jiasheng Si, Deyu Zhou
摘要
Argumentative essay generation (AEG) is a complex task that requires advanced semantic understanding, logical reasoning, and organized integration of perspectives. Despite showing a promising performance, current efforts often overlook the dynamical and hierarchical nature of structural argumentative planning, and struggle with flexible rhetorical expression, leading to limited argument divergence and rhetorical optimization. Inspired by human debate behavior and Bitzer's rhetorical situation theory, we propose a debate-driven rhetorical framework for argumentative writing. The uniqueness lies in three aspects: (1) it dynamically assesses the divergence of viewpoints and progressively reveals the hierarchical outline of arguments based on a depththen-breadth paradigm, improving the perspective divergence within argumentation; (2) simulates human debate through iterative defenderattacker interactions, improving the logical coherence of arguments; (3) incorporates Bitzer's rhetorical situation theory to flexibly select appropriate rhetorical techniques, enabling the rhetorical expression. Experiments on four benchmarks validate that our approach significantly improves logical depth, argumentative diversity, and rhetorical persuasiveness over existing state-of-the-art models 1 .
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper3
- iRULER: Intelligible Rubric-Based User-Defined LLM Evaluation for RevisionJingwen Bai, Wei Soon Cheong, Philippe Muller, Brian Y. LimCHI 2026 · 被引用 1 次
- IS-CoT: Breaking the Long-form Generation Collapse via Interleaved Structural ThinkingZechen Sun, Yuyang Sun, Zecheng Tang, Juntao Li 等ACL 2026
- Beyond Static Artifacts: An Evolutionary Framework for Synthetic Claim GenerationYeqing Teng, Jiasheng Si, Shuxia Lin, Linhai Zhang 等ACL 2026
它引用的顶会 Paper12
- Tree of Thoughts: Deliberate Problem Solving with Large Language ModelsShunyu Yao, Dian Yu, Jeffrey Zhao, Izhak Shafran 等NeurIPS 2023 · 被引用 5,068 次
- CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model SocietyGuohao Li, Hasan Hammoud, Hani Itani, Dmitrii Khizbullin 等NeurIPS 2023 · 被引用 1,975 次
- BARTScore: Evaluating Generated Text as Text GenerationWeizhe Yuan, Graham Neubig, Pengfei LiuNeurIPS 2021 · 被引用 1,143 次
- Adversarial NLI: A New Benchmark for Natural Language UnderstandingYixin Nie, Adina Williams, Emily Dinan, Mohit Bansal 等ACL 2020 · 被引用 602 次
- Debating with More Persuasive LLMs Leads to More Truthful AnswersAkbir Khan, John Hughes, Dan Valentine, Laura Ruis 等ICML 2024 · 被引用 244 次
相关 Paper
- AEG: Argumentative Essay Generation via A Dual-Decoder Model with Content PlanningJianzhu Bao, Yasheng Wang, Yitong Li, Fei Mi 等EMNLP 2022 · 被引用 1 次
- Prove Your Point!: Bringing Proof-Enhancement Principles to Argumentative Essay GenerationRuiyu Xiao, Lei Wu, Yuhang Gou, Weinan Zhang 等EMNLP 2024 · 被引用 3 次
- InspireDebate: Multi-Dimensional Subjective-Objective Evaluation-Guided Reasoning and Optimization for DebatingFuyu Wang, Jiangtong Li, Kun Zhu, Changjun JiangACL 2025 · 被引用 3 次
- Debatable Intelligence: Benchmarking LLM Judges via Debate Speech EvaluationNoy Sternlicht, Ariel Gera, Roy Bar-Haim, Tom Hope 等EMNLP 2025 · 被引用 1 次
- DEFINED: A Data-Efficient Computational Framework for Fine-Grained Creativity Assessment in Debate ScenariosTongzhou Yu, Mingjia Li, Hong Qian, Wenkai Wang 等KDD 2026 · 被引用 1 次
