ArtemLykov/LLM-MARS_QA

该数据集由Skoltech的智能空间机器人实验室开发，用于训练基于游戏结果的问答模块的LLM。该模型是多代理人工智能系统的一部分，用于LLM-MARS论文中描述的狗机器人。数据集的任务类别是问答，语言为英语，标签包括机器人技术，规模类别为100K<n<1M。

This dataset was developed by a team from Skoltechs Intelligent Space Robotics Laboratory. It was used to train an LLM for the Question Answering Module based on game results. This model is part of a multi-agent artificial intelligence system for the dog robot described in the LLM-MARS paper. The task category of the dataset is question-answering, the language is English, the tags include robotics, and the size category is 100K<n<1M.

原始信息汇总

数据集概述

基本信息

• 许可证: cc-by-4.0
• 任务类别: 问答
• 语言: 英语
• 标签: 机器人学
• 数据集规模: 100K<n<1M

开发团队

• 开发机构: Skoltechs Intelligent Space Robotics Laboratory

用途

• 应用场景: 用于训练基于游戏结果的问答模块的大型语言模型（LLM）。
• 关联项目: 该模型是用于狗机器人的多智能体人工智能系统的一部分，相关内容在LLM-MARS论文中描述。

引用信息

论文引用

bibtex @misc{lykov2023llmmarslargelanguagemodel, title={LLM-MARS: Large Language Model for Behavior Tree Generation and NLP-enhanced Dialogue in Multi-Agent Robot Systems}, author={Artem Lykov and Maria Dronova and Nikolay Naglov and Mikhail Litvinov and Sergei Satsevich and Artem Bazhenov and Vladimir Berman and Aleksei Shcherbak and Dzmitry Tsetserukou}, year={2023}, eprint={2312.09348}, archivePrefix={arXiv}, primaryClass={cs.RO}, url={https://arxiv.org/abs/2312.09348}, }

数据集引用

bibtex @misc{LLM-MARS_QA, title={LLM-MARS_QA}, author={Artem Lykov and Maria Dronova and Nikolay Naglov and Mikhail Litvinov and Sergei Satsevich and Artem Bazhenov and Vladimir Berman and Aleksei Shcherbak and Dzmitry Tsetserukou}, year={2024}, publisher={Hugging Face}, howpublished={url{https://huggingface.co/datasets/ArtemLykov/LLM-MARS_QA}} }