This repository contains the code for the research paper "Revolutionizing Chatbot Responsiveness: Automated History Context Selector for Multi-turn Dialogue Systems in Large Language Models". The codebase is designed to implement and evaluate the automated context selection mechanism for enhancing the responsiveness of chatbots in multi-turn conversations.
- Automated Context Selector: Innovative algorithm for identifying the most relevant historical context.
- Scalability: Compatible with LLMs for robust dialogue systems.
Documentation for the project can be found in this project.
We welcome contributions! Please read CONTRIBUTING.md for details on our code of conduct and the process for submitting pull requests.
This project is licensed under the MIT License.
If you find our work useful in your research, please consider citing:
@misc{
author = {Weicheng Wanga, Xiaoliang Chena, Hongyun Zhang, Duoqian Miao, Xiaolin Qin, Peng Lu},
title = {Revolutionizing Chatbot Responsiveness: Automated History Context Selector for Multi-turn Dialogue Systems in Large Language Models},
year = {2024},
}
For questions or support, feel free to reach out:
- Email: weichengwang@stu.xhu.edu.cn