Update README.md

README.md

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----
-license: apache-2.0
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+---
+license: apache-2.0
+language: en
+tags:
+- persuasion
+- llm
+- dataset-generation
+- multi-agent
+- dialogue
+- nlp
+---
+
+# 🧠 LLM-based Persuasion Simulator
+
+Official model and repository for the following papers:
+
+> **Communication Makes Perfect: Persuasion Dataset Construction via Multi-LLM Communication**  
+> *NAACL 2025 (Main Conference)*  
+> [https://aclanthology.org/2025.naacl-long.203/](https://aclanthology.org/2025.naacl-long.203/)
+
+> **Communication is All You Need: Persuasion Dataset Construction via Multi-LLM Communication**  
+> *arXiv preprint, February 2025*  
+> [arXiv:2502.08896](https://arxiv.org/abs/2502.08896)
+
+Both versions describe the same multi-LLM communication framework for generating persuasive dialogue datasets,  
+with the NAACL 2025 paper being the peer-reviewed and finalized version.
+
+---
+
+## 📘 Overview
+
+This repository provides the **LLM-based persuasion simulation framework** introduced in our paper.  
+The framework enables automated generation of high-quality persuasive dialogues through **multi-agent communication among large language models (LLMs)**,  
+covering diverse linguistic and strategic dimensions of persuasion.
+
+**Key features:**
+- Multi-LLM communication to enhance dialogue fluency, coherence, and diversity  
+- Fine-grained control over persuasion strategies  
+- Modular design for flexible extension and reproducibility  
+- Applied to construct the *PersuaSim* and *PersuaSim-Culture* datasets  
+
+---
+
+## 📂 Code Repository
+
+💻 **Full implementation and scripts are available at:**  
+👉 [https://github.com/HF-heaven/LLM-based_persuasion_simulator](https://github.com/HF-heaven/LLM-based_persuasion_simulator)
+
+---
+
+## 🧩 Citation
+
+If you find this work useful, please cite:
+
+```bibtex
+@inproceedings{ma2025communication,
+  title={Communication Makes Perfect: Persuasion Dataset Construction via Multi-LLM Communication},
+  author={Ma, Weicheng and Zhang, Hefan and Yang, Ivory and Ji, Shiyu and Chen, Joice and Hashemi, Farnoosh and Mohole, Shubham and Gearey, Ethan and Macy, Michael and Hassanpour, Saeed and others},
+  booktitle={Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)},
+  pages={4017--4045},
+  year={2025}
+}